Electronic device and method for controlling the same

Abstract

An electronic device is provided. A method of controlling the electronic device includes: displaying at least one sentence, analyzing the at least one sentence by using at least one character and the at least one sentence including the at least one character when a user input regarding at least one character of the at least one displayed sentence is received, selecting a character set included in the at least one sentence based on the analysis result, and displaying the selected character set separately from other characters included in the at least one sentence.

Description

Technical Field

[0001] The present disclosure relates to a method for selecting content to be displayed on a display of an electronic device including a display. Background Art

[0002] Recently, electronic devices can provide various contents through a display. For example, an electronic device can display an image, a video, or text on the display. The electronic device can support an operation of searching for additional information corresponding to a user input to select content to be displayed on the display.

[0003] For example, the electronic device can magnify an image or provide photographic information for selecting an image in response to a user input. In addition, the electronic device can provide the meaning or related information of text for selecting the text in response to a user input. Summary of the Invention

[0004] Technical Problem

[0005] When a user selects some characters displayed on a display to search for the meaning or related information of the characters, the user may experience inconvenience in precisely adjusting the start and end points of the characters to be searched.

[0006] Accordingly, various embodiments of the present invention are provided to easily display a character range when a user selects characters. Brief Description of the Drawings

[0007] FIGS. 1A and 1B illustrate a state of identifying and displaying a plurality of characters on an electronic device according to a user's selection according to an embodiment.

[0008] Figure 2 is a schematic block diagram of an electronic device according to an embodiment.

[0009] Figure 3 illustrates a state in which a general score of a character set is used to identify one character set among a plurality of character sets on an electronic device according to an embodiment.

[0010] Figure 4 illustrates a state in which an electronic device identifies a character set including a plurality of characters by using a grammatical structure of a sentence according to an embodiment.

[0011] Figure 5 illustrates a state in which an electronic device identifies a character set including a plurality of non-adjacent characters.

[0012] Figure 6 illustrates a state of identifying one character set among a plurality of character sets on an electronic device by using a search history according to an embodiment.

[0013] Figure 7Shows a state in which an electronic device selects a search category considering the sentence content.

[0014] Figure 8 Shows an embodiment in which an electronic device according to an embodiment displays a selected area notification object.

[0015] Figure 9 Is a block diagram of an electronic device according to various embodiments.

[0016] Figure 10 Is a flowchart showing a state in which an electronic device according to an embodiment identifies and displays multiple characters.

[0017] Figure 11 Is a flowchart showing a state in which an electronic device according to an embodiment, associated with a server, identifies and displays multiple characters.

[0018] Figure 12 Is a block diagram of an electronic device in a network environment according to various embodiments. Detailed Description

[0019] According to an aspect of the present disclosure, an electronic device includes a display, a processor, and a memory, wherein the memory stores instructions that cause the processor to: control the display to display at least one sentence received in response to a user input regarding at least one character of at least one displayed sentence, analyze at least one sentence by using at least one character and at least one sentence including at least one character in response to the user input, select a character set included in the at least one sentence according to the analysis result, and display the selected character set to be distinguished from other characters included in the at least one sentence.

[0020] In an embodiment, the character set may include at least one character corresponding to the user input.

[0021] In an embodiment, the character set may include multiple characters.

[0022] In an embodiment, the character set may include multiple characters adjacent to each other.

[0023] In an embodiment, the instructions may cause the processor to: when performing a search by using the identified character set, identify a search category based on the content of other character sets included in the at least one sentence.

[0024] In an embodiment, the instructions may cause the processor to: obtain a plurality of character set candidates, each character set candidate including a character selected corresponding to the user input and at least one adjacent character, obtain a plurality of candidate sentences respectively corresponding to the plurality of character set candidates; and analyze the obtained plurality of candidate sentences, select one candidate sentence, and select a character set corresponding to the selected one candidate sentence.

[0025] In an embodiment, the instructions may enable a processor to analyze at least one sentence based on a coherence score obtained according to a correlation between a replaced character set and other characters or other words included in a plurality of candidate sentences when the plurality of character set candidates are replaced by other character sets.

[0026] In an embodiment, the instructions may enable a processor to analyze at least one sentence based on a generality score obtained according to the usage frequency and importance of characters or words included in each of the plurality of character set candidates.

[0027] In an embodiment, the instructions may enable a processor to analyze at least one sentence according to a grammatical feature of a sentence constituent and based on a classification of the sentence constituent of at least one sentence including at least one character selected corresponding to a user input.

[0028] In an embodiment, the instructions may enable a processor to use a search history previously stored in a memory when analyzing at least one sentence.

[0029] In an embodiment, the electronic device may further include a communication module, wherein the instructions enable the processor to control the communication module to send at least one character and at least one sentence including at least one character to a server, and receive a result of selecting a character set included in the at least one sentence by analyzing the at least one sentence by the server using the at least one character and the at least one sentence including the at least one character.

[0030] According to another aspect of the present disclosure, a server includes a communication module, a processor, and a memory, wherein the memory stores instructions that enable the processor to control the communication module to receive at least one character and a sentence including the at least one character from an external device. In response to the reception, the processor analyzes the sentence by using the at least one character and the sentence including the at least one character, selects a character set included in the sentence according to an analysis result, and controls the communication module to send the selected character set to the external device.

[0031] According to another aspect of the present disclosure, a control method of an electronic device includes: displaying at least one sentence, when receiving a user input of at least one character regarding the at least one displayed sentence, analyzing the at least one sentence by using the at least one character and the at least one sentence including the at least one character, selecting a character set included in the at least one sentence according to an analysis result, and displaying the selected character set to be distinguished from other characters included in the at least one sentence.

[0032] According to another aspect of the present disclosure, a computer-readable recording medium stores instructions that, when executed on a computer, display at least one sentence, analyze the at least one sentence by using at least one character and the at least one sentence including the at least one character when receiving a user input regarding at least one character of the displayed at least one sentence, select a character set included in the at least one sentence according to the analysis result, and display the selected character set to be distinguished from other characters included in the at least one sentence.

[0033] Embodiments of the present disclosure

[0034] Since the present disclosure allows various variations and multiple embodiments, the embodiments will be illustrated in the drawings and described in detail in the written description. However, this is not intended to limit the present disclosure to a specific embodiment, and it should be understood that various modifications, equivalents, and / or alternatives that do not depart from the spirit and technical scope of the present disclosure are also included in the present disclosure. In the description of the present disclosure, some detailed explanations of related technologies are omitted when it is considered that they may unnecessarily obscure the essence of the present disclosure.

[0035] In this specification, it should be understood that terms such as "including", "having", and "containing" are intended to indicate the presence of features, numbers, steps, actions, components, parts, or combinations thereof disclosed in the specification, and are not intended to exclude the possibility of the presence or addition of one or more other features, numbers, steps, actions, components, parts, or combinations thereof.

[0036] In this specification, expressions such as "A or B", "at least one of A and / or B", or "at least one or more of A and / or B" may include all possible combinations of the items listed together. For example, expressions such as "A or B", "at least one of A and B", or "at least one of A or B" may represent: (1) including at least one A; (2) including at least one B; or (3) including all cases of both at least one A and at least one B.

[0037] Terms such as "first" and "second" are only used herein to describe various components regardless of order and / or importance, and are used to distinguish one component from another, but the components are not limited by these terms. For example, a first user device and a second user device may represent different user devices regardless of order and / or importance. For example, without departing from the correct scope of the present disclosure, a first component may be referred to as a second component, and vice versa.

[0038] In addition, the terms "module", "unit", and "component" described in the specification may represent a unit that processes at least one function or operation, and the unit may be embodied by hardware, software, or a combination of hardware and software. In addition, except in cases where each of the module, unit, and component needs to be implemented by separate specific hardware, a plurality of "modules", "units", and "components", etc. may be integrated in at least one module or chip to be implemented as at least one processor.

[0039] In this specification, when a component (e.g., a first component) is (operatively or communicatively) coupled or connected to another component (e.g., a second component), the component contacts or connects to the other component directly or through at least one other component (e.g., a third component). Conversely, when a component (e.g., a first component) is described as being directly connected or directly coupled to another component (e.g., a second component), the component should be construed as being directly connected to the other component without any other component (e.g., a third component) intervening therebetween.

[0040] The terms used in this specification are for explaining specific embodiments and are not for limiting the present disclosure. Thus, expressions used in the singular form in the specification also include those used in the plural form, unless clearly stated otherwise in the context. Unless otherwise defined, all terms (including technical or scientific terms) used herein have the same meanings as those commonly understood by those of ordinary skill in the art to which the present disclosure pertains. Terms defined in commonly used dictionaries are construed to have meanings that match the meanings in the context of the related art, and are not construed as being ideal or overly formal unless clearly defined otherwise. In some cases, even terms defined herein may not be construed as being exclusive of the embodiments of the present disclosure.

[0041] FIGS. 1A and 1B illustrate states of identifying and displaying a plurality of characters according to a selection by a user on an electronic device.

[0042] According to an embodiment, the electronic device 10 may display various contents on the display 11. For example, the electronic device 10 may display contents such as images, videos, texts, etc. on the display 11. The display 11 may include a touch screen display. In response to a user input selecting various contents displayed on the display 11, the electronic device 10 may provide new information related to the selected content, or identify a part of the selected content and provide the identified part to the user separately from another part of the content.

[0043] Referring to reference numeral 1-a in FIG. 1A, the electronic device 10 may display characters on the display 11.

[0044] For example, the electronic device 10 may display characters on the display 11 by executing a document file (e.g., a word document file, a Portable Document Format (PDF) file, etc.) stored in the electronic device 10. For example, an operating system (OS) running on the electronic device 10 may control a text file execution application, and the text file execution application may execute a word document file to execute the word document file selected by the user to be displayed on the display 11.

[0045] Alternatively, the electronic device 10 may display characters on the display 11 by accessing a web server to download an online magazine, an online newspaper, etc. For example, the OS running on the electronic device 10 may download an online magazine, an online newspaper, etc. from the web server in the form of a file format. The OS may control an execution application capable of executing the downloaded file to execute the document file to be displayed on the display 11.

[0046] Alternatively, when the web server accesses the electronic device 10 to control the display 11 of the electronic device 10, an online magazine, an online newspaper, etc. may be displayed on the web server.

[0047] Referring to reference numeral 1-b in FIG. 1A, the electronic device 10 may receive a user touch input 105 to select at least one of the characters displayed on the display 11.

[0048] According to an embodiment, the user may select at least one character to perform an additional search for a specific word, a specific phrase, a specific clause, or a specific sentence included in the article displayed on the display 11. For example, the electronic device 10 may receive a user touch input 105 to select characters from the words displayed on the display 11, i.e., 110, to select characters, i.e., 112. According to an embodiment, the user touch input 105 may be a long touch input that touches 112 for a preset time or longer, or a multi-touch input that touches 112 multiple times within a set time. However, the user touch input 105 is not limited thereto.

[0049] According to various embodiments, when the user manipulates a physical key included in the electronic device 10, the electronic device 10 may receive an input for selecting 112 from the word (i.e., 110).

[0050] According to an embodiment, in response to a user input for selecting at least one character displayed on the display 11, the electronic device 10 may analyze a sentence including at least one character by using the sentence and at least one character, and select a character set included in the sentence according to the analysis result.

[0051] For example, the electronic device 10 may obtain a plurality of character set candidates corresponding to a user input, the character set candidates including the selected character and at least one adjacent character, obtain a plurality of candidate sentences respectively corresponding to the plurality of character set candidates, analyze the obtained candidate sentences, select one candidate sentence, and select a character set corresponding to the selected one candidate sentence.

[0052] Specifically, in response to a user selection, the electronic device 10 may obtain a character set including the selected character and at least one adjacent character. Obtaining the character set may mean, for example, determining a character set that includes the selected character and characters that appear within a preset distance from the selected character. The electronic device 10 may obtain a plurality of character set candidates by repeatedly performing the operation of obtaining the character set.

[0053] For example, the electronic device 10 may determine to include of etc. as character set candidates, where the character selected by the user.

[0054] According to an embodiment, the electronic device 10 may obtain a plurality of candidate sentences respectively corresponding to the plurality of character set candidates, analyze the obtained candidate sentences, select one candidate sentence, and select a character set corresponding to the selected one candidate sentence.

[0055] For example, the electronic device 10 may obtain a coherence score of the character set candidate by analyzing the obtained candidate sentences.

[0056] Analyzing a sentence may mean, for example, the electronic device 10 analyzes the correlation between the characters or words forming the sentence. Or, analyzing a sentence may mean an operation such as, for example, identifying whether the relationship between the characters or words forming the sentence is continuous or discontinuous. Or, analyzing a sentence may mean, for example, analyzing the grammatical relationship between the characters or words forming the sentence. Or, analyzing a sentence may mean, for example, analyzing the grammatical role of the characters or words forming the sentence. Or, analyzing a sentence may mean performing the above analysis processes sequentially or simultaneously.

[0057] According to an embodiment, the coherence score may be a score given to the character set as a result of the analysis of the above sentence. For example, the coherence score may be a score given to the character set when the electronic device 10 calculates the degree of coherence in the relationship between the character set and other characters in the candidate sentence.

[0058] For example, the electronic device 10 may obtain including 112 (It is a candidate sentence), where 112 is a character selected by the user. The operation of obtaining a candidate sentence including the character selected by the user may mean, for example, determining a candidate sentence by using an artificial intelligence (AI) model, and the artificial intelligence (AI) model is trained to distinguish the boundary between sentences by using an end word for terminating a sentence.

[0059] The electronic device 10 may obtain a plurality of characters including 112 within the range of the obtained candidate sentence as a character set. For example, the electronic device 10 may determine a plurality of characters including 112 (which is the character selected by the user) 112(which is the character selected by the user) etc. as a character set. However, the present disclosure is not limited thereto. For example, the electronic device 10 may obtain a plurality of characters including 112 outside the range of the obtained candidate sentence as a character set. In this case, the electronic device 10 may exclude a character set that does not form a word from the obtained character set. 112 from the obtained character set.

[0060] For example, as shown in reference numeral 1-c of FIG. 1B, the electronic device 10 may obtain In addition, the electronic device 10 may obtain as a second candidate character set and obtain as a third candidate character set.

[0061] According to various embodiments, the electronic device 10 may obtain, for example, a first candidate character set, a second candidate character set, and a third candidate character set, and combine the obtained candidate character sets with another character in the sentence to generate a new candidate character set.

[0062] According to an embodiment, the electronic device 10 may obtain a coherence score for a plurality of candidate character sets based on an analysis of a candidate sentence including the obtained character set. For example, when the obtained candidate character set is replaced by another word, the electronic device 10 may distinguish whether the replaced word has independence or dependence related to other words or characters included in the sentence.

[0063] According to an embodiment, the electronic device 10 may select one character set from a plurality of candidate character sets according to the coherence score. One character set selected by the electronic device 10 may be, for example, a character set having a high coherence score according to the sentence analysis result. A character set having a high coherence score may be, for example, a character set very likely to be selected by the user.

[0064] Specifically, the electronic device 10 may apply the operation to a sentence instead of the first character set candidate, the second character set candidate, and the third character set candidate.

[0065] For example, when the coherence score is close to 1, this may mean that the character set candidate is likely to be used by being connected to other characters included in the candidate sentence. In addition, when the coherence score is closer to 0, this may mean that the character set candidate is very unlikely to be used by being connected to other characters included in the candidate sentence.

[0066] For example, the electronic device 10 may apply a word instead of the first character set candidate to the candidate sentence, and obtain the candidate sentence

[0067] The electronic device 10 may apply a word instead of the second character set candidate and the third character set candidate to the candidate sentence, and obtain the candidate sentence and

[0068] The electronic device 10 may apply as a non-existent character set, although it is not grammatically incorrect in the candidate sentence, and gives a coherence score of 0.72.

[0069] The electronic device 10 may apply as a less frequently used character set, where the postposition is grammatically omitted in the candidate sentence, and gives a coherence score of 0.65.

[0070] The electronic device 10 may apply as a character set that is combinable and has no grammatical errors in the candidate sentence, and gives a coherence score of 0.78.

[0071] Based on the recognition result, the electronic device 10 may recognize as the first character set candidate having the maximum coherence score. In other words, the coherence score may mean the fluency in terms of the grammar or meaning of the replacement character set related to the other character sets of the candidate sentence when one character set is replaced by another character set in the candidate sentence.

[0072] According to various embodiments, the electronic device 10 that analyzes candidate sentences to obtain a coherence score may be one of the embodiments of the present disclosure. For example, the electronic device 10 may analyze a phrase to which a character set belongs, a clause to which a character set belongs, a paragraph to which a character set belongs, or a document to which a character set belongs. In other words, the electronic device 10 may analyze a plurality of characters forming a sentence, phrase, clause, paragraph, or document, and select a character set included in the characters.

[0073] Referring to reference numeral 1-d of FIG. 1B, the electronic device 10 may display the selected area notification object on the display 11 to display the identified character set so as to be distinguishable from other characters.

[0074] For example, the electronic device 10 may display the area 120 adjacent to the character set including the identified character by changing the color of the area 120. However, the present disclosure is not limited thereto. For example, the electronic device 10 may display the character in a color different from the color of other characters, or by changing the thickness of the character.

[0075] According to various embodiments, when the area 120 adjacent to the is displayed by changing its color, the electronic device 10 may receive a user input to select another character displayed on the display 11, for example of In this case, the electronic device 10 terminates the display of the area 120 adjacent to the by changing its color, and sequentially displays the area adjacent to the by changing its color.

[0076] Thus, according to an embodiment of the present disclosure, when a user attempts to perform an additional search or the like by selecting a word display on the display 11, the inconvenience of adjusting the start point and the end point of each of the words, phrases, and clauses to select a desired word, phrase, or clause can be reduced. For example, as described above, when a user selects only one character, the character set including the selected character and very likely to be selected by the user is recognized and displayed separately from other characters in consideration of the meaning and / or structure of the sentence including the selected character.

[0077] Figure 2 is a schematic block diagram of an electronic device according to an embodiment.

[0078] Referring to Figure 2 , the electronic device 10 may include a processor 210, a display 220, and a memory 230. The electronic device 10 may further include a communication module 240. However, the present disclosure is not limited thereto. The electronic device 10 may include more constituent elements or exclude some constituent elements to perform the functions of the electronic device 10.

[0079] According to an embodiment, the processor 210 may control the overall operation of the electronic device 10. For example, the processor 210 may execute a stored program by controlling the memory 230, or retrieve or store necessary information.

[0080] According to an embodiment, the processor 210 may control the display 220 to display at least one sentence, receive a user input regarding at least one character of the displayed sentence, analyze the sentence by using the at least one character and the sentence including the at least one character, select a character set included in the sentence in response to the user input according to the analysis result, and display the selected character set to be distinguished from other characters included in the sentence.

[0081] According to various embodiments, the electronic device 10 may include multiple processors. For example, the electronic device 10 may include a general-purpose processor and an AI dedicated processor.

[0082] The AI dedicated processor may be, for example, a processor that is more integrated, has less latency, has better performance, or has more resources than the general-purpose processor.

[0083] According to an embodiment, compared with the general-purpose processor, the AI dedicated processor may quickly and efficiently process a large amount of calculations required to generate, update, or apply an AI model.

[0084] According to an embodiment, the general-purpose processor may control the display 220 to display at least one sentence, receive a user input to select at least one character of the displayed sentence, and select a sentence including the selected character.

[0085] The AI dedicated processor may receive the selected character and the sentence including the selected character from the general-purpose processor, analyze the sentence by using the selected character and the sentence including the selected character, select a character set included in the sentence according to the analysis result, and send the selected character set to the general-purpose processor. For example, the AI dedicated processor may obtain multiple character set candidates including the selected character, generate a coherence score regarding the character set candidates, and select one character set.

[0086] The general-purpose processor may display the received character set to be distinguished from other characters.

[0087] However, the operations performed by each processor are not limited thereto. For example, the electronic device 10 may allow each processor to perform operations separately in various forms.

[0088] According to an embodiment, the display 220 may display an image, video, text, and / or execution screen of an application. When the display 220 is implemented as a touch screen display, in addition to an output device, the display 220 may also be used as an input device. The display 220 may include at least one of a liquid crystal display, a thin film transistor-liquid crystal display, an organic light emitting diode, a flexible display, a 3D display, an electrophoretic display, etc.

[0089] According to an embodiment, the display 220 may display at least one sentence under the control of the processor 210 and receive a user input to select at least one character included in the displayed sentence. In addition, the display 220 may display a set of identified characters under the control of the processor 210 to distinguish them from other characters.

[0090] According to an embodiment, the memory 230 may include at least one type of storage medium, such as a flash memory, a hard disk, a multimedia card microcomputer, a card type memory, such as an SD or XD memory, a random access memory (RAM), a static random access memory (SRAM), a read only memory (ROM), an electrically erasable programmable ROM (EEPROM), a programmable ROM (PROM), a magnetic memory, a magnetic disk, an optical disk, etc.

[0091] According to an embodiment, the memory 230 may store instructions configured to cause the processor 210 to control the display 220 to display at least one sentence, receive a user input regarding at least one character of the displayed sentence, analyze the sentence by using at least one character and the sentence including at least one character in response to the user input, select a character set included in the sentence according to the analysis result, and display the selected character set to distinguish it from other characters included in the sentence.

[0092] According to an embodiment, the communication module 240 may connect the electronic device 10 to an external device, such as a server, another electronic device, under the control of the processor 210. Depending on the performance and structure of the electronic device 10, the communication module 240 may include one of the constituent elements implementing various wired or wireless communication methods, such as a wireless local area network (LAN), Bluetooth, and a wired Ethernet.

[0093] Figure 3 A state according to an embodiment is shown, in which a generality score of a character set is used to identify one character set among a plurality of character sets on an electronic device.

[0094] According to an embodiment, the electronic device 10 may calculate a generality score by considering the frequency of use of a character set including words, phrases, or clauses in a sentence, paragraph, or document, and store the generality score as a database in the memory 230. The generality score may be a score for determining whether a character set set in a sentence, paragraph, or document is likely to be selected by a user for searching.

[0095] For example, at least one of the frequency of use of the character set, the degree of importance of the character set, and the possibility of additional search using the character set may be considered to determine the generality score. However, the factors to be considered in determining the generality score are not limited thereto.

[0096] The generality score may be determined, for example, based on whether a user is more likely to select a character set to obtain additional information, because although the character set is not commonly used in a sentence, paragraph, or document, when used in a sentence, paragraph, or document, the character set has an important meaning and is thus used as an important meaning in the sentence, paragraph, or document.

[0097] The generality score may be determined, for example, based on whether many people are likely to search for additional information about the character set, because although the character set is not commonly used in a sentence, paragraph, or document, when used in a sentence, paragraph, or document, many people are curious about the character set.

[0098] The generality score may be close to 1, for example, when the frequency is relatively high and the probability of searching for additional information is relatively low. In addition, when the frequency is relatively low and the probability of searching for additional information is relatively high, the generality score may be close to 0.

[0099] Referring Figure 3 to the reference numeral 3-a in the attached drawings, the electronic device 10 may store the generality score for a character set including words, phrases, or clauses. For example, the electronic device 10 may, based on a plurality of sentences or documents collected and classified as data into a plurality of character sets, give 0.73456 points to give 0.52679 points to give 0.41181 points to give 0.01220 points to

[0100] Referring Figure 3 to the reference numeral 3-b in the attached drawings, the electronic device 10 may identify that is a sentence including (which is a character selected by the user). The electronic device 10 may obtain a plurality of characters including in the sentence as a character set. In addition, the electronic device 10 may obtain, in the sentence, those related to the character set including The character set adjacent to the character set. For example, the electronic device 10 may obtain and as character set candidates.

[0101] According to an embodiment, the electronic device 10 may, based on the generality scores of the obtained multiple character set candidates, identify a character set with a high probability of searching for additional information by identifying it as having a low frequency.

[0102] As shown by reference numeral 1-d in FIG. 1B, the electronic device 10 may display the selected area 120 on the display 11 to display the identified character set separately from other characters.

[0103] Figure 4 Shows the state in which an electronic device according to an embodiment identifies a character set including multiple characters by using the grammatical structure of a sentence

[0104] According to an embodiment, the electronic device 10 may classify the sentence constituent elements of a sentence including the characters selected by the user according to the grammatical features of the sentence constituent elements. The electronic device 10 may store a sentence analysis algorithm in the memory 230, and the sentence analysis algorithm can hierarchically classify the sentence constituent elements (such as words, phrases or clauses) included in a sentence into levels such as nouns, post-words or suffixes by using, for example, a tree structure.

[0105] The electronic device 10 may hierarchically classify the words, phrases or clauses in the sentence by grammatical analysis of the identified sentence. For example, the electronic device 10 may identify at least one of a noun phrase, a verb phrase, an adjective phrase and an adverb phrase from the identified sentence. In addition, the electronic device 10 may identify the part of speech of the character set classified from the identified sentence. The part of speech identified by the electronic device 10 may include, for example, a common noun, a suffix and a postposition, but is not limited thereto.

[0106] For example, the electronic device 10 may identify which is a sentence including as the characters selected by the user. The electronic device 10 may perform grammatical analysis on the identified sentence.

[0107] For example, the electronic device 10 may classify as the first phrase in the sentence. In addition, the electronic device 10 may classify as the second phrase.

[0108] The electronic device 10 may classify in the first phrase as the third phrase, and classify The part-of-speech recognition of is recognized as the fourth phrase, and the part-of-speech recognition of is recognized as the second part of speech, the part-of-speech recognition of is recognized as the fourth part of speech, and the part-of-speech recognition of is recognized as the fifth part of speech. For example, the third phrase may be a noun phrase, and the fourth phrase is a noun phrase. For example, the first part of speech may be a common noun, the second part of speech may be a common noun, the third part of speech may be a suffix derived from a noun, the fourth part of speech may be a common noun, and the fifth part of speech may be a postposition.

[0109] The electronic device 10 may recognize this expression as the fifth phrase. The electronic device 10 may respectively recognize from the fifth phrase the and part-of-speech of as the sixth part of speech, the seventh part of speech, and the eighth part of speech, and recognize the part-of-speech of as the ninth part of speech. For example, the fifth phrase may be a noun phrase in the form of an adjective. For example, the sixth part of speech, the seventh part of speech, and the eighth part of speech may be common nouns, and the ninth part of speech may be a postposition.

[0110] According to an embodiment, the electronic device 10 may recognize a character set included in the tree structure 410, which is the smallest level to which the character selected by the user belongs. For example, the electronic device 10 may recognize as a character set very likely to be selected by the user.

[0111] According to various embodiments, the electronic device 10 may recognize only the part composed of nouns except for the postposition part in the recognized character set as the character set. For example, the electronic device 10 may recognize in (which corresponds to the postposition part) except for as a character set very likely to be selected by the user.

[0112] Figure 5 illustrates a state in which the electronic device recognizes a character set including a plurality of non-adjacent characters.

[0113] Referring to Figure 5 the reference numeral 5-a in the drawing, the electronic device 10 may display characters on the display 11. For example, the characters may be a part of a newspaper article displayed on a web browser. However, the characters may not be limited to newspaper articles and may include various contents using characters.

[0114] According to an embodiment, the electronic device 10 may receive a user input 505 to select at least one of the characters displayed on the display 11.

[0115] According to an embodiment, the user may select at least one character to perform an additional search for a specific word, specific phrase, specific clause, or specific sentence included in the text displayed on the display 11. For example, the electronic device 10 may receive a user touch input to select the word 510 “down” displayed on the display 11.

[0116] Referring Figure 5 to the reference numeral 5-b in the attached drawings, the electronic device 10 may obtain a plurality of character set candidates by repeatedly performing an operation of obtaining a character set including the selected character and at least one adjacent character in response to the user selection. In addition, the electronic device 10 may obtain a plurality of candidate sentences respectively corresponding to the obtained character set candidates, analyze the obtained candidate sentences to select one candidate sentence, and identify the character set corresponding to the selected one candidate sentence as the character set very likely to be searched for additional information by the user.

[0117] For example, the electronic device 10 may obtain the sentence “I had the equations down pat for my final exam” including “down” (which is the character selected by the user). The electronic device 10 may obtain a plurality of characters including “down” as one character set.

[0118] For example, the electronic device 10 may obtain a plurality of character set candidates including “down”, “down pat”, “equations down pat”, or “had down pat”. In this case, the electronic device 10 may obtain a character set including characters not directly adjacent to the selected character (e.g., “had down pat”) as a character set candidate.

[0119] According to an embodiment, the electronic device 10 may analyze a sentence including the obtained character set and a sentence including the obtained characters by using the obtained characters, and identify one character set from the plurality of character set candidates.

[0120] For example, when a character set candidate is replaced by other words, the electronic device 10 may identify a sentence having an appropriate sentence structure and meaning, and thus identify one of the plurality of character set candidates as the character set very likely to be selected by the user for searching.

[0121] For example, the electronic device 10 may identify a character set by using the search history made by a user who uses the electronic device 10. Alternatively, the electronic device 10 may identify one character set among multiple character set candidates by using the general score of the character set. Alternatively, the electronic device 10 may identify one character set among multiple character set candidates by using the grammatical structure of a sentence.

[0122] Referring Figure 5 to reference numeral 5-b in, the electronic device 10 may identify "had down pat" among multiple character set candidates as a character set highly likely to be selected by the user for searching. For example, the electronic device 10 may identify "had down pat" as an idiom by using the grammatical structure, and identify "had down pat" as a character set highly likely to be searched for additional information because although the character set is not frequently used, when used in a sentence, the character set has an important meaning.

[0123] Referring Figure 5 to reference numeral 5-c in, the electronic device 10 may display the selected area notification object on the display 11 to display the identified one character set so as to be distinguishable from other characters.

[0124] For example, the electronic device 10 may display the color of the area 520 to be different from adjacent colors with respect to the character set including the identified characters "haddown pat", where the area 520 includes an area 521 adjacent to "had" and an area 522 adjacent to "down pat". However, the present disclosure is not limited thereto. For example, the electronic device 10 may display the characters "had down pat" in a color different from other characters, or display them by changing the thickness of the characters.

[0125] Figure 6 illustrates a state of identifying one character set among multiple character sets on an electronic device by using a search history according to an embodiment.

[0126] According to an embodiment, the electronic device 10 may store the search history made by the user using the electronic device 10 in the memory 230 as a database. For example, the electronic device 10 may display a web browser on the display 11 that can perform information search in response to user input. The user may input a word, phrase, clause, or sentence to be searched through the web browser including a search window and check the search results.

[0127] According to an embodiment, when obtaining multiple characters including the characters selected corresponding to the user selection as one character set, the electronic device 10 may use the previously stored search history.

[0128] For example, in reference numeral 1-c of FIG. 1B, the electronic device 10 may obtain as a first character set candidate. In addition, the electronic device 10 may obtain as a second character set candidate, and obtain as a third character set candidate.

[0129] The electronic device 10 may analyze a sentence including the obtained character sets by using the obtained character sets and sentences including the obtained character sets, and when identifying one of the multiple character sets, check the search history previously stored in the electronic device 10.

[0130] Referring to Figure 6 , the electronic device 10 may check from the search history that input the character set at 13:34 on April 11, 2018 and provided its search results. In addition, the electronic device 10 may check from the search history that input the character set at 11:27 on April 11, 2018 and provided its search results.

[0131] According to an embodiment, the electronic device 10 may use the history of the user inputting a disease-related character set to identify the first character set candidate among the first to third character set candidates that matches the name of the disease as the character set very likely to be selected by the user for searching.

[0132] Figure 7 Illustrates the state where the electronic device considers the sentence content to select a search category.

[0133] According to an embodiment, the electronic device 10 may use the content of a sentence that includes a character selected by the user in a state where a search is performed in a web browser by using the identified character set. The electronic device 10 may determine a search category in the sentence including the character selected by the user based on the meaning of the identified character set and other words. In this case, other words for determining the search category may be determined based on, for example, a close relationship with the identified character set, the type of part of speech, importance in the sentence, etc. In addition, the electronic device 10 may consider the content of adjacent sentences of the sentence including the character selected by the user to determine the search category.

[0134] For example, the electronic device 10 may, in response to the user selecting in (which is a word included in the first sentence), identify as the character set very likely to be selected by the user. When the user requests a search for When, the electronic device 10 can perform a search through a web browser. In this case, the electronic device 10 can first search within a category related to books or novels by referring to words such as or included in the first sentence.

[0135] According to an embodiment, the electronic device 10 can, in response to a user selection of among (as a word included in the second sentence), identify as a character set very likely to be selected by the user. When the user requests a search for , the electronic device 10 can perform a search through a web browser. In this case, the electronic device 10 can first search within a category related to amusement parks by referring to words such as or included in the second sentence.

[0136] According to an embodiment, the electronic device 10 can, in response to a user selection of of (which is a word included in the third sentence), identify as a character set very likely to be selected by the user. When the user requests a search for , the electronic device 10 can perform a search through a web browser. In this case, the electronic device 10 can first search within a category related to movies by referring to words such as and the like included in the second sentence.

[0137] Thus, according to an embodiment of the present disclosure, the electronic device 10 can provide search results suitable for the user's intention by considering the content of the sentence in which the character set is located.

[0138] Figure 8 An embodiment of an electronic device displaying a selected area notification object according to an embodiment is shown.

[0139] Referring to Figure 8 with reference numeral 8-a, the electronic device 10 can display characters on the display 11. For example, the characters can be part of a newspaper article displayed on a web browser. However, the characters are not limited to newspaper articles and can include various contents using characters.

[0140] According to an embodiment, the electronic device 10 can receive a user input 805 to select at least one of the characters displayed on the display 11.

[0141] According to an embodiment, a user may select at least one character to perform an additional search for a specific word, specific phrase, specific clause, or specific sentence included in an article displayed on a display 11. For example, an electronic device 10 may receive a user touch input to select a word displayed on the display 11 810 of 812.

[0142] Referring to Figure 8 reference numeral 8-b in the accompanying drawings, the electronic device 10 may obtain a plurality of character sets by repeating an operation of obtaining a plurality of characters including the selected character as a character set in response to the user selection.

[0143] For example, the electronic device 10 may obtain, as a sentence including 812, where 812 is the character selected by the user. The electronic device 10 may obtain a plurality of characters including 812 as a character set.

[0144] For example, the electronic device 10 may obtain as a first character set candidate. In addition, the electronic device 10 may obtain as a second character set candidate and obtain as a third character set candidate.

[0145] According to an embodiment, the electronic device 10 may display character set candidates on the display 11 and identify one of the character set candidates as the character set on which the user performs an additional information search based on the user selection.

[0146] For example, the electronic device 10 may display a candidate list including first to third character set candidates in the form of a pop-up window 820 on the display 11. The electronic device 10 may display the selected character set to distinguish it from other characters according to a user input for selecting one of the displayed character set candidates.

[0147] Figure 9 is a block diagram of an electronic device according to various embodiments.

[0148] Referring to Figure 9 , the electronic device 901 may include a character / location selection module 910, a candidate selection module 912, a candidate scoring / re-ranking module 914, a boundary generation module 916, a previous device / previous user configuration 918, a search history database 920, and a keyword dictionary 922. The electronic device 901 may include the electronic device 10 of FIG. 1A.

[0149] According to an embodiment, the character / position selection module 910 may receive a user input to select a character from a sentence. The character / position selection module 910 may obtain the position of the selected character in the sentence or the relative position in the sentence.

[0150] According to an embodiment, the candidate selection module 912 may obtain a character set including the selected character and at least one adjacent character. The candidate selection module 912 may obtain a plurality of character sets by repeatedly performing the process.

[0151] According to an embodiment, the candidate scoring / re-ranking module 914 may obtain a plurality of candidate sentences respectively corresponding to the obtained character sets, and analyze the obtained candidate sentences. For example, the candidate scoring / re-ranking module 914 may analyze the meaning of the candidate sentences and give a coherence score.

[0152] According to various embodiments, the candidate scoring / re-ranking module 914 may send the obtained result to the candidate selection module 912. The candidate selection module 912 may perform again the process of obtaining a plurality of characters including the selected character as a character set by reflecting the sent result.

[0153] According to an embodiment, when performing the above operations, the candidate selection module 912 and the candidate scoring / re-ranking module 914 may use the data received from the search history database 920 and the keyword dictionary 922.

[0154] For example, the search history database 920 may store the search history of the user using the electronic device 901 for searching. When performing the operations of obtaining and identifying the character set, the candidate selection module 912 and the candidate scoring / re-ranking module 914 may assign weights to the character sets related to the fields that the user of the electronic device 901 is generally interested in by referring to the search history received from the search history database 920.

[0155] In addition, the keyword dictionary 922 may store general scores regarding the character sets. When performing the operations of obtaining and identifying the character set, the candidate selection module 912 and the candidate scoring / re-ranking module 914 may assign weights to the less frequently used but significant character sets by referring to the general scores received from the keyword dictionary 922.

[0156] The previous device / previous user configuration 918 may store basic information of the electronic device 901. The basic information may include, for example, the memory capacity, CPU power, display size, etc. of the electronic device 901. The electronic device 10 may adjust the amount of data stored in the search history database 920 and the keyword dictionary 922 according to the basic information. Alternatively, when transferring the coherence score to the character set, the electronic device 10 may adjust the data range for using the data stored in the search history database 920 and the keyword dictionary 922 according to the basic information.

[0157] According to various embodiments, the electronic device 901 may receive and use data from an external device. For example, the electronic device 901 may receive a specific search history used by multiple users from the general search history database 930 and use the specific search history when giving a coherence score to the character set.

[0158] Alternatively, the electronic device 901 may receive a general score from the general keyword dictionary 940 and use the general score when giving a coherence score to the character set.

[0159] According to various embodiments, the character / position selection module 910, the candidate selection module 912, the candidate scoring / re-ranking module 914, and the boundary generation module 916 may be terms for constituent elements involved in performing at least one function or operation. Therefore, these constituent elements may be stored in a memory (e.g., Figure 2 the memory 230) in the form of a software combination or a combination of instructions or implemented by a processor (e.g., Figure 2 the processor 210).

[0160] According to various embodiments, the previous device / previous user configuration 918, the search history database 920, and the keyword dictionary 922 may correspond to Figure 2 the memory 230.

[0161] According to various embodiments, the general search history database 930 and the general keyword dictionary 940 may correspond to at least one server that communicates with the electronic device 901.

[0162] The AI-related functions according to the present disclosure can be operated by a processor and a memory. The processor may include one or more processors. In this state, the one or more processors may include general-purpose processors such as a central processing unit (CPU), an application processor (AP), a digital signal processor (DSP), etc., a graphics-specific processor such as a graphics processing unit (GPU) or a vision processing unit (VPU), or an AI-specific processor such as a neural processing unit (NPU). The one or more processors can be controlled to process input data according to a predetermined operation rule or an AI model stored in the memory. Alternatively, when the one or more processors are AI-specific processors, the AI-specific processors can be designed to have a hardware structure dedicated to processing a specific AI model.

[0163] The predefined operation rule or AI model is characteristically formed through learning. What is formed through learning can mean that as the basic AI model is trained using a plurality of learning data through a learning algorithm, a predefined operation rule or AI model configured to perform a desired feature or purpose is formed. The learning can be performed in the device itself, where the AI according to the present disclosure is executed, or through a separate server and / or system. Examples of the learning algorithm can include supervised learning, unsupervised learning, semi-supervised learning, or reinforcement learning, but are not limited to the above examples.

[0164] The AI model can include a plurality of neural network layers. Each of the plurality of neural network layers can have a plurality of weight values, and perform neural network operations through an operation between the operation result of the previous layer and the plurality of weight values. The plurality of weight values of the plurality of neural network layers can be optimized through the learning result of the AI model. For example, the plurality of weight values can be updated to reduce or lower the loss or cost value obtained by the AI model during the learning process. The artificial neural network can include a deep neural network (DNN), such as a convolutional neural network (CNN), a deep neural network (DNN), a recurrent neural network (RNN), a restricted Boltzmann machine (RBM), a deep belief network (DBN), a bidirectional recurrent deep neural network (BRDNN), a deep Q network, etc., but the present disclosure is not limited thereto.

[0165] According to an embodiment, at least one AI model, such as a coherence recognition model, a generality recognition model, or a sentence analysis model, can be trained.

[0166] For example, when a plurality of sentences are input into the AI model, the AI model can be trained to estimate the words that appear beside a set of consecutive words that make up each of the plurality of sentences.

[0167] For example, consecutive phrases and words adjacent to each phrase can be extracted from an arbitrary sentence, and the extracted phrases and words can be used as training data. Thus, the AI model can estimate the naturalness of the sentence, such as a coherence score or a generality score.

[0168] In addition, according to various embodiments, when multiple sentences are input into the AI model, the AI model can be trained to estimate multiple words located at a predetermined distance from each word constituting the multiple sentences. In addition, when multiple sentences are input into the AI model, the AI model can be trained to estimate a single word located at the same distance from the words constituting the multiple sentences.

[0169] For example, multiple words located at a predetermined distance from a single word included in a certain sentence can be extracted, and the extracted words can be used as training data. In addition, a single word located at the same distance from the multiple words can be extracted from a certain sentence, and the extracted word can be used as training data.

[0170] The inherent directionality of each word can be obtained by using the trained result, and the similarity of words (such as a coherence score or a generality score) can be estimated by using the directionality.

[0171] In addition, according to various embodiments, when multiple sentences and their corresponding sentence structures are input into the AI model, the AI model can be trained to estimate the sentence structures constituting the multiple sentences.

[0172] According to various embodiments, a coherence recognition model can be trained such that the coherence recognition model has a criterion for recognizing the coherence score of a character set included in a sentence or a document. The coherence recognition model can be trained to have a criterion regarding which training data is used for the coherence recognition model to obtain the coherence score of the character set included in a sentence or a document, or how to recognize the coherence score of the character set included in a sentence or a document by using the training data.

[0173] According to various embodiments, the coherence recognition model can be trained by using multiple sentences or multiple documents as training data. For example, the training data can include all types of documents and sentences, such as newspaper articles, editorials, novels, papers, etc.

[0174] According to various embodiments, the trained coherence recognition model can obtain the coherence score of a character set included in a sentence or a document based on various types of recognition data. The trained coherence recognition model can obtain the coherence score of the character set from at least one input sentence or document.

[0175] According to various embodiments, the response or feedback of a user to the coherence score output from the coherence recognition model can be used to update the coherence recognition model. Accordingly, the coherence recognition model can increase the probability of obtaining the coherence score of a character set according to the user's disposition.

[0176] According to various embodiments, a generality recognition model can be trained to have criteria for obtaining a generality score of a character set included in a sentence or a document. The generality recognition model can be trained to have criteria regarding which training data is used to obtain the generality score of a character set included in a sentence or a document, or how the coherence score of a character set included in a sentence or a document is identified by using the training data.

[0177] According to various embodiments, the generality recognition model can be trained by using multiple sentences or multiple documents as training data. For example, the training data can include all types of sentences and documents, such as newspaper articles, editorials, novels, papers, etc.

[0178] According to various embodiments, the trained generality recognition model can obtain the generality score of a character set included in a sentence or a document based on various types of recognition data. The trained generality recognition model can obtain the generality score of a character set from at least one input sentence or document.

[0179] According to various embodiments, the response of a user to the generality score output from the generality recognition model can be used to update the generality recognition model. Accordingly, the generality recognition model can increase the probability of obtaining the generality score of a character set according to the user's disposition.

[0180] According to various embodiments, a sentence analysis model can be trained to have criteria for classifying constituent elements (e.g., nouns, verbs, suffixes, postpositions, etc.) included in a sentence. The sentence analysis model can be trained to have criteria regarding which training data is used to classify the constituent elements included in a sentence, or how the constituent elements included in a sentence are identified by using the training data.

[0181] According to various embodiments, the sentence analysis model can be trained by using the results of classifying sentences and words included in a sentence according to constituent elements using training data.

[0182] For example, the sentence analysis model can be trained by using the following results: the results of classifying a sentence where is a noun, is a pronoun, is a noun, is a postposition, and is a verb.

[0183] According to various embodiments, a trained sentence analysis model may classify constituent elements included in a sentence based on various types of recognition data. At least one constituent element included in an input sentence may be classified by using the trained sentence analysis model.

[0184] According to various embodiments, a user's response to the result output from the sentence analysis model may be used to update the sentence analysis model.

[0185] For example, when the input sentence is provided, the sentence analysis model may obtain the classification result of as a pronoun, as a postposition, and as an adjective.

[0186] A coherence recognition model, a generality recognition model, and a sentence analysis model may be established in consideration of the application field of the recognition model, the purpose of learning, the computer performance of the device, etc. The coherence recognition model, the generality recognition model, and the sentence analysis model may be models based on, for example, a neural network. The coherence recognition model, the generality recognition model, and the sentence analysis model may include, for example, a neural network model or a deep learning model developed from a neural network model.

[0187] Figure 10 is a flowchart of an electronic device according to an embodiment for recognizing and displaying the states of a plurality of characters.

[0188] In operation 1110, the electronic device 10 may display at least one sentence.

[0189] For example, the electronic device 10 may display a newspaper article displayed on a web browser on the display 220.

[0190] In operation 1120, when a user input for selecting at least one character included in the sentence is received, the electronic device 10 may analyze the sentence by using the at least one character and the sentence including the at least one character.

[0191] For example, when the display 220 includes a touch screen display, the electronic device 10 may receive a user input for selecting a character by touching an area of the touch screen display.

[0192] For example, in response to the user selection, the electronic device 10 may obtain a character set including the selected character and at least one adjacent character. The electronic device 10 may obtain a plurality of character set candidates by repeatedly performing the operation of obtaining the character set.

[0193] The electronic device 10 may obtain a plurality of candidate sentences respectively corresponding to the plurality of character set candidates, and may analyze the obtained candidate sentences.

[0194] For example, the electronic device 10 may obtain a coherence score of the character set candidate by analyzing the obtained candidate sentences. The coherence score as a result of analyzing the candidate sentences may be a score given to the character set. For example, the coherence score may be a score calculated and given by the electronic device 10 based on how coherent the character set is with other characters in the sentence.

[0195] According to various embodiments, the electronic device 10 may generate a new character set candidate by combining the obtained character set with another character during the process of obtaining one character set of a plurality of character set candidates.

[0196] In operation 1130, the electronic device 10 may select a character set included in the sentence according to the analysis result. One character set selected by the electronic device 10 is, for example, the analysis result of the candidate sentence, and the candidate sentence may be a character set with a high coherence score.

[0197] In operation 1140, the electronic device 10 may display the selected character set separately from other characters included in the sentence.

[0198] For example, the electronic device 10 may change and display the color of the area adjacent to the recognized character set.

[0199] Figure 11 It is a flowchart of a state in which an electronic device according to an embodiment, which is associated with a server, recognizes and displays a plurality of characters.

[0200] In operation 1210, the electronic device 10 may display at least one sentence.

[0201] In operation 1220, when a user input regarding at least one character of the displayed sentence is received, the electronic device 10 may obtain a sentence including at least one character.

[0202] In operation 1230, the electronic device 10 may send at least one character and the sentence including at least one character to the server 20.

[0203] In operation 1240, the server 20 may analyze the sentence by using at least one character and the sentence including at least one character. In operation 1250, the server 20 may select a character set included in the sentence according to the analysis result. For example, the server 20 may obtain a plurality of character set candidates including characters corresponding to the user input, obtain a plurality of candidate sentences corresponding to the obtained character sets, and select one character set by analyzing the obtained candidate sentences.

[0204] In operation 1260, the server 20 may send the selected character set to the electronic device 10.

[0205] In operation 1270, the electronic device 10 may display the received character set separately from other characters included in the sentence.

[0206] According to various embodiments, when the server 20 is connected to the electronic device 10 and controls the display 220 of the electronic device 10 to display characters, in response to a user input of at least one character, the server 20 may recognize a sentence including the at least one character. In this case, based on the analysis result, the server 20 may control the display 220 of the electronic device 10 to display the character set included in the sentence separately from other characters included in the sentence.

[0207] Figure 12 is a block diagram of an electronic device 1301 in a network environment 1300 according to various embodiments. The electronic device 1301 may include the electronic device 10 of FIG. 1A. Referring to Figure 12 , in the network environment 1300, the electronic device 1301 may communicate with the electronic device 1302 via a first network 1398 (e.g., a short-range wireless communication network), or communicate with the electronic device 1304 or the server 1308 via a second network 1399 (e.g., a long-range wireless communication network). According to an embodiment, the electronic device 1301 may communicate with the electronic device 1304 via the server 1308. According to an embodiment, the electronic device 1301 may include a processor 1320, a memory 1330, an input device 1350, a sound output device 1355, a display device 1360, an audio module 1370, a sensor module 1376, an interface 1377, a haptic module 1379, a camera module 1380, a power management module 1388, a battery 1389, a communication module 1390, a user identification module 1396, or an antenna module 1397. In an embodiment, in the electronic device 1301, at least one of the above-described components may be omitted, such as the display device 1360 or the camera module 1380, or one or more other components may be added. In an embodiment, some of the constituent elements may be implemented as one integrated circuit. For example, the sensor module 1376 (e.g., a fingerprint sensor, an iris sensor, or an illuminance sensor) may be implemented by being embedded in the display device 1360 (e.g., a display).

[0208] The processor 1320 may control at least one of the other constituent elements of the electronic device 1301 connected to the processor 1320, such as hardware or software constituent elements, by executing software such as, for example, the program 1340, and perform various data processing or operations. According to an embodiment, as at least a part of the data processing or operation, the processor 1320 may load instructions or data received from other constituent elements (e.g., the sensor module 1376 or the communication module 1390) onto the volatile memory 1332, process the instructions or data stored in the volatile memory 1332, and store the resulting data in the non-volatile memory 1334. According to an embodiment, the processor 1320 may include a main processor 1321 (e.g., a central processing unit or an application processor) and an auxiliary processor 1323 (e.g., a graphics processing unit, an image signal processor, a sensor hub processor, or a communication processor), which may operate independently or completely. Additionally or alternatively, the auxiliary processor 1323 may be configured to use less power than the main processor 1321 or be assigned to a specified function. The auxiliary processor 1323 may be implemented separately from the main processor 1321 or as a part of the main processor 1321.

[0209] The auxiliary processor 1323 may control at least some of the functions or states related to at least one of the constituent elements of the electronic device 1301, such as, for example, the display device 1360, the sensor module 1376, or the communication module 1390, when the main processor 1321 is in an inactive state (e.g., a sleep state), or may control at least some of the functions or states related to at least one of the constituent elements of the electronic device 1301 together with the main processor 1321 when the main processor 1321 is in an active state (e.g., an application execution state). According to an embodiment, the auxiliary processor 1323 (e.g., an image signal processor or a communication processor) may be implemented as a part of other function-related constituent elements (e.g., the camera module 1380 or the communication module 1390).

[0210] The memory 1330 may store various data used by at least one of the constituent elements of the electronic device 1301 (e.g., the processor 1320 or the sensor module 1376). The data may include, for example, software such as the program 1340, and input data or output data regarding instructions related thereto. The memory 1330 may include a volatile memory 1332 or a non-volatile memory 1334.

[0211] The program 1340 may be stored in the memory 1330 as software, and may include, for example, an operating system 1342, middleware 1344, or an application 1346.

[0212] The input device 1350 may receive instructions or data for components of the electronic device 1301 (e.g., the processor 1320) from the outside of the electronic device 1301 (e.g., from a user). The input device 1350 may include, for example, a microphone, a mouse, or a keyboard.

[0213] The sound output device 1355 may output a sound signal to the outside of the electronic device 1301. The sound output device 1355 may include, for example, a speaker or a receiver. The speaker may be used for general purposes such as multimedia reproduction or recording reproduction, and the receiver may be used for receiving incoming calls. According to an embodiment, the receiver may be implemented separately from the speaker or as part of the speaker.

[0214] The display device 1360 may visually provide information to the outside of the electronic device 1301, for example, to a user. The display device 1360 may include, for example, a display, a hologram device, or a projector, and a control circuit for controlling any of the devices. According to an embodiment, the display device 1360 may include a touch circuit configured to sense a touch, or a sensor circuit configured to measure the intensity of a force generated by the touch, such as a pressure sensor.

[0215] The audio module 1370 may convert sound into an electrical signal or convert an electrical signal back into sound. According to an embodiment, the audio module 1370 may obtain sound through the input device 1350, or output sound directly or wirelessly through the sound output device 1355 or an external electronic device (e.g., an electronic device 1302 such as a speaker or headphones) connected to the electronic device 1301.

[0216] The sensor module 1376 may detect the operating state of the electronic device 1301, such as power or temperature, or the external environmental state, such as the user state, and generate an electrical signal or a data value corresponding to the detected state. According to an embodiment, the sensor module 1376 may include, for example, a gesture sensor, a gyro sensor, a barometric pressure sensor, a magnetic sensor, an acceleration sensor, a grip sensor, a proximity sensor, a color sensor, an infrared (IR) sensor, a biometric sensor, a temperature sensor, a humidity sensor, or an illuminance sensor.

[0217] The interface 1377 may support one or more specified protocols for the electronic device 1301 to be directly or wirelessly connected to an external electronic device (e.g., the electronic device 1302). According to an embodiment, the interface 1377 may include, for example, a high-definition multimedia interface (HDMI), a universal serial bus (USB) interface, an SD card interface, or an audio interface.

[0218] The connection end 1378 may include a connector through which the electronic device 1301 is physically connected to an external electronic device, such as the electronic device 1302. According to an embodiment, the connection end 1378 may include, for example, an HDMI connector, a USB connector, an SD card connector, or an audio connector, such as a headphone connector.

[0219] The haptic module 1379 may convert an electrical signal into a mechanical stimulus, such as vibration or motion, that can be recognized by a user through touch or kinesthesia, or into an electrical stimulus. According to an embodiment, the haptic module 1379 may include, for example, a motor, a piezoelectric device, or an electrical stimulation device.

[0220] The camera module 1380 may capture still images and videos. According to an embodiment, the camera module 1380 may include one or more lenses, an image sensor, an image signal processor, or a flash.

[0221] The power management module 1388 may manage the power provided to the electronic device 1301. According to an embodiment, the power management module 1388 may be implemented as at least a part of, for example, a power management integrated circuit (PMIC).

[0222] The battery 1389 may provide electric power to at least one component element of the electronic device 1301. According to an embodiment, the battery 1389 may include, for example, a non-rechargeable primary battery, a rechargeable secondary battery, or a fuel cell.

[0223] The communication module 1390 may establish a direct communication channel (e.g., a wired communication channel) or a wireless communication channel between the electronic device 1301 and an external electronic device (e.g., the electronic device 1302, the electronic device 1304, or the server 1308), and support communication through the established communication channel. The communication module 1390 may include one or more communication processors that operate independently of the processor 1320, such as an application processor, and support direct communication, such as wired communication or wireless communication. According to an embodiment, the communication module 1390 may include a wireless communication module 1392, such as a cellular communication module, a short-range wireless communication module, or a global navigation satellite system (GNSS) communication module, or may include a wired communication module 1394, such as a LAN communication module or a power line communication module. Any corresponding communication module of the communication module may communicate with an external electronic device through a first network 1398 (e.g., a short-range communication network such as Bluetooth, WiFi Direct, or infrared data association (IrDA)) or a second network 1399 (e.g., a long-range communication network such as a cellular network, the Internet, or a computer network (such as a LAN or a WAN)). These various types of communication modules may be implemented by being integrated into one component element, such as a single chip, or as multiple separate component elements, such as multiple chips. The wireless communication module 1392 may check and approve the electronic device 1301 in a communication network such as the first network 1398 or the second network 1399 by using user information (e.g., international mobile subscriber identity (IMSI)) stored in the user identification module 1396.

[0224] The antenna module 1397 may transmit a signal or power to the outside, e.g., an external electronic device, or receive the signal or power from the outside. According to an embodiment, the antenna module 1397 may include one or more antennas, and at least one antenna suitable for a communication method of a communication network such as the first network 1398 or the second network 1399 may be selected by, for example, the communication module 1390. The signal or power may be transmitted or received between the communication module 1390 and an external electronic device through the selected at least one antenna.

[0225] At least some of the component elements may be interconnected with each other by a communication method between peripheral devices (e.g., a bus, general-purpose input and output (GPIO), serial peripheral interface (SPI), or mobile industry processor interface (MIPI)), and exchange signals (e.g., instructions or data) therebetween.

[0226] According to an embodiment, instructions or data may be transmitted or received between an external electronic device 1301 and an electronic device 1304 via a server 1308 connected to a second network 1399. Each of the electronic devices 1302 and 1304 may be the same as or different from the electronic device 1301. The server 1308 may include a communication module (not shown), a processor (not shown), and a memory (not shown). However, the present disclosure is not limited thereto, and the server 1308 may further include constituent elements or omit some constituent elements. The server 1308 may include Figure 11 server 20. According to an embodiment, all or some of the operations performed in the electronic device 1301 may be performed in one or more external devices such as the electronic devices 1302 and 1304 or the server 1308. For example, when the electronic device 1301 is assumed to automatically perform a function or service, or perform a function or service in response to a request from a user or another device, the electronic device 1301 may not perform the function or service but request one or more external devices to perform at least a part of the function or service, or may request one or more external devices to perform at least a part of the function or service in addition to performing the function or service. One or more external devices that have received the request may perform at least a part of the requested function or service, or perform an additional function or service related to the request, and send the result of the execution to the electronic device 1301. The electronic device 1301 may process the result as it is or additionally, and provide the result as at least a part of a response to the request.

[0227] Alternatively, the electronic device 1301 may send at least one character specified by a user selection and a sentence including at least one character to the server 1308, and receive a result of selecting a character set included in the sentence by analyzing the sentence using at least one character and the sentence received by the server 1308. To this end, for example, cloud computing, distributed computing, or client-server computing technologies may be used.

[0228] Various embodiments of the present disclosure may be implemented as software (e.g., program 1340) including one or more instructions stored in a storage medium, such as internal memory 1336 or external memory 1338 that can be read by a machine (e.g., electronic device 1301). For example, a processor (e.g., processor 1320) of a device (e.g., electronic device 1301) may retrieve and execute at least one of the one or more instructions stored in the storage medium. This enables the device to perform at least one function in accordance with the at least one retrieved instruction. The one or more instructions may include code generated by a compiler or code executable by an interpreter. A device-readable storage medium may be provided in the form of a non-transitory storage medium. "Non-transitory" may mean that the storage medium is a tangible device and does not include signals, such as electromagnetic waves, and the term does not distinguish between cases where data is stored semi-permanently in the storage medium and cases of temporary storage.

[0229] According to an embodiment, a method according to various embodiments disclosed in the present disclosure may be provided by being included in a computer program product. A computer program product is a product traded between a seller and a buyer. The computer program product may be distributed in the form of a device-readable storage medium, such as a compact disc read-only memory (CD-ROM), or through an application store (e.g., PlayStore TM ) or distributed directly or online between two user devices (e.g., smartphones), such as downloading or uploading. For online distribution, at least a part of the computer program product may be at least temporarily stored in a device-readable storage medium such as the memory of a manufacturer's server, an application store's server, or a relay server, or may be temporarily generated from a device-readable storage medium.

[0230] According to various embodiments, each of the above-described components, such as a module or a program, may include a single or multiple objects. According to various embodiments, in the above-described components, one or more components or operations may be omitted, or one or more other components or operations may be added. Alternatively or additionally, multiple components (e.g., modules or programs) may be integrated into one component. In this case, the integrated component may perform one or more functions of each component in the same or similar manner as the one or more functions performed by the components before integration. According to various embodiments, operations performed by a module, a program, or other components may be executed sequentially, in parallel, repeatedly, or heuristically, one or more operations may be executed within another or omitted, or one or more other operations may be added.

Claims

1. An electronic device, comprising: A display; A processor; And A memory, Wherein, the memory stores instructions that enable the processor to perform the following operations: Control the display to display at least one sentence; Receive user input regarding at least one character of the at least one displayed sentence; In response to the user input, analyze the at least one sentence; Obtain a plurality of character set candidates, each character set candidate including the at least one character and at least one adjacent character; According to the analysis result of the at least one sentence, select a character set included in the at least one sentence from the plurality of character set candidates; and Display the selected character set separately from other characters included in the at least one sentence; Wherein, the at least one sentence is analyzed according to the classification of the sentence constituent elements of the at least one sentence, and the at least one sentence includes the at least one character selected according to the grammatical features of the sentence constituent elements and corresponding to the user input.

2. The electronic device according to claim 1, wherein, The character set includes a plurality of characters arranged adjacent to each other.

3. The electronic device according to claim 1, wherein, The instructions enable the processor to: when performing a search by using the selected character set, identify a search category based on the content of other character sets included in the at least one sentence.

4. The electronic device according to claim 1, wherein, The instructions enable the processor to: Obtain a plurality of candidate sentences respectively corresponding to the plurality of character set candidates; And Analyze the obtained plurality of candidate sentences, select one candidate sentence, and select a character set corresponding to the selected one candidate sentence from among the plurality of character set candidates.

5. The electronic device according to claim 4, wherein, The instructions enable the processor to: when the plurality of character set candidates are replaced by other character sets, analyze the at least one sentence based on a coherence score obtained according to the correlation between the replaced character set and other characters or other words included in the plurality of candidate sentences.

6. The electronic device according to claim 4, wherein, The instructions enable the processor to: analyze the at least one sentence based on a generality score obtained according to the usage frequency and the importance of characters or words included in each of the plurality of character set candidates.

7. The electronic device according to claim 1, wherein, The instructions enable the processor to: use a search history previously stored in the memory when analyzing the at least one sentence.

8. The electronic device according to claim 1, further comprising a communication module, Among them, The instructions enable the processor to: control the communication module to send the at least one character and the at least one sentence including the at least one character to a server, and receive a result of selecting a character set included in the at least one sentence by the server analyzing the at least one sentence by using the at least one character and the at least one sentence including the at least one character.

9. A server, comprising: A communication module; A processor; And A memory, Wherein, the memory stores instructions that enable the processor to perform the following operations: Control the communication module to receive at least one character and a sentence including the at least one character from an external device, wherein, corresponding to the reception, the processor analyzes the sentence; Obtain a plurality of character set candidates, each character set candidate including the at least one character and at least one adjacent character; Select, based on the analysis result of the at least one sentence, the character set included in the sentence from the plurality of character set candidates; and Control the communication module to send the selected character set to the external device; wherein the at least one sentence is analyzed according to the classification of the sentence constituent elements of the at least one sentence, and the at least one sentence includes the at least one character selected corresponding to the user input according to the grammatical features of the sentence constituent elements.

10. A method for controlling an electronic device, the method comprising: Display at least one sentence; When receiving a user input regarding at least one character of the at least one displayed sentence, analyze the at least one sentence; Obtain a plurality of character set candidates, each character set candidate including the at least one character and at least one adjacent character; Select, based on the analysis result of the at least one sentence, the character set included in the at least one sentence from the plurality of character set candidates; And Display the selected character set separately from other characters included in the at least one sentence; wherein the at least one sentence is analyzed according to the classification of the sentence constituent elements of the at least one sentence, and the at least one sentence includes the at least one character selected corresponding to the user input according to the grammatical features of the sentence constituent elements.

11. A computer-readable recording medium storing instructions that, when executed on a computer, cause the computer to: Display at least one sentence; When receiving a user input regarding at least one character of the at least one displayed sentence, analyze the at least one sentence; Obtain a plurality of character set candidates, each character set candidate including the at least one character and at least one adjacent character; Select, based on the analysis result of the at least one sentence, the character set included in the at least one sentence from the plurality of character set candidates; And Display the selected character set separately from other characters included in the at least one sentence; wherein the at least one sentence is analyzed according to the classification of the sentence constituent elements of the at least one sentence, and the at least one sentence includes the at least one character selected corresponding to the user input according to the grammatical features of the sentence constituent elements.

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