110 results about "Adjective" patented technology

A method is disclosed wherein the webpages listed in the result set of a search engine is sorted according to the relevance of the webpages to a list of prioritised search terms. Search terms which are phrases that are delimited by prepositions are considered search terms with high priority. Search terms which nouns are set to high priority. Search terms which are adjectives, verbs, auxiliary verbs, articles, conjunctions, pronouns and prepositions are set to low priority.

A method and system for semantically analyzing unstructured data in a customer feedback is provided. The method includes extracting data related to customer feedback from one or more input sources. The method further includes assigning weights to the one or more input sources and extracting relevant text from the feedback data. Further, sentences are detected from the customer feedback and are annotated. Thereafter, relevant adjectives are determined and are associated with sentence types. A rating is calculated for each sentence of the relevant text and output is provided in a pre-determined format.

Document comparisons can be performed at a semantic level by utilizing a rules base in which groups of rules are applied sequentially. In one implementation, (1) syntactic rules are applied to a document to form a tagged sequence in which individual words are tagged with their syntactic categories, (2) ambiguity rules are applied to the tagged sequence to resolve ambiguities, thereby providing a resolved tag sequence, (3) grammar rules are applied to the resolved tagged sequence to determine semantic roles of individual tagged words, thereby providing a role-specific resolved tagged sequence, and (4) property rules are applied to match properties (e.g., adjectives) with the words they modify, thereby providing a semantic feature structure. The semantic feature structure is then compared to at least one other structure.

A method for extracting opinion-related patterns includes receiving a corpus of reviews, the reviews each including an explicit rating of a topic. The reviews are partitioned among a predefined plurality of classes, based on the ranking. Syntactic relations are identified in each review. The syntactic relations may each include an adjective and a noun. A set of patterns is generated, each of the patterns having at least one of the identified syntactic relations as an instance and the patterns clustered into a set of clusters based on a set of features. At least one of the features is based on occurrences, in the predefined classes, of the instances of the patterns. A polarity is assigned to ones of the clusters and propagated to patterns in the respective clusters. The polarity-labeled patterns can each be instantiated as a contextual rule for opinion mining.

A recommendation method includes receiving a user's review of an item that includes a textual comment. Deficient features of the reviewed item are identified from the text by applying a set of extraction patterns. Each pattern is satisfied when a term in the text, which is associated in a structured terminology with one of a predefined set of features, is in a syntactic relation with another term in the text, such as a polar adjective or expression of a wish or a lack. When such a pattern is satisfied, the corresponding feature is considered a deficient feature. Feature attributes of the reviewed item are compared with corresponding feature attributes of a set of items to identify any improved items whose attribute for the deficient feature is better than that for the reviewed item. The improved item or items can be recommended to the user or to others reading the review.

An approach for building an ontology is provided. Based on a grammar, extracted complex triples are syntactically transformed to identify core terms. The syntactically transformed complex triples are semantically transformed into simplified triples referring to new terms that conceptualize the core adjectives, adverbs and verbs, and assigning the core terms to respective definitions and keys in a reference ontology, thereby retaining the semantics of the complex triples. Based on a meta-schema of the reference ontology, an enrichment transformation of the simplified triples is performed to create simplified and enriched triples by adding relations derived from a correspondence each term in the simplified triples has with the reference ontology and by adding representations of semantics of reference ontology definitions of the terms. The simplified and enriched triples are stored as an ontology representing knowledge in an application providing the free-form text from which the complex triples were extracted.

A structured natural language query and knowledge system is provided to allow a user who lacks programming skills to enter a database query or a rule in the form of a structured natural language sentence. The scope of the sentence is preferably defined by an improved object relational query language, an object relational algebra, or both. Command and conditions that appear in natural language form are defined with corresponding formal query texts. A user is prompted to compose a structured natural language sentence using the defined commands and conditions. The user-selected command and its arguments appear as the verb phrase of a structured natural language sentence. The user-selected conditions and their parameters appear as the adjective phrases of the sentence. The sentence is parsed and changed into a translated formal query text for formal database query and rule processing.

A system, method, and computer program product for generating a polar vocabulary are provided. The method includes extracting textual content from each review in a corpus of reviews. Each of the reviews includes an author's rating, e.g., of a specific product or service to which the textual content relates. A set of frequent nouns is identified from the textual content of the reviews. Adjectival terms are extracted from the textual content of the reviews. Each adjectival term is associated in the textual content with one of the frequent nouns. A polar vocabulary including at least some of the extracted adjectival terms is generated. A polarity measure is associated with each adjectival term in the vocabulary which is based on the ratings of those reviews from which the adjectival term was extracted.

A system for coding and decoding languages that includes a first set of computerized databases and each of database storing a predetermined number of indexed information elements (such as words) and a second set of computerized databases wherein each database includes a predetermined number of structural arrangements for using the information elements. The indexed information elements are classified by the component class of a sentence or phrase. They may be classified as verbs, adjectives, etc. and this holds true for the same indexed entry for the different databases for a particular information element. The system decodes the information elements in a sentence, or phrase and matches a corresponding structural arrangement in a given language which holds for the other language.

The invention discloses an SVM based micro-blog emotion classification method fusing various kinds of emotion resources. The method includes the following steps: constructing relevant dictionaries including an emotion dictionary, a negation dictionary, and a degree adverb dictionary; performing pretreatment on different corpora, performing word segmentation and part-of-speech tagging on the corpora, and performing sentence structure analysis; comparing the segmented words and positive and negative dictionaries to acquire initial word polarity, comparing words ahead of emotion words and the word degree grade dictionary and the negation dictionary to acquire modifier weight, and multiplying the initial word polarity by the modifier weight to acquire emotion scores of each micro-blog; extracting features such as nouns, verbs, adjectives, positive and negative emotion words, degree adverb weights, emotion scores, privatives and specific symbols from part-of-speech features, emotion features, sentence pattern features, and semantic features; and inputting the extracted features into an Libsvm to perform model training so as to acquire a training model. The method can achieve emotion 5-grade classification of micro-blogs, and can accurately and roundly acquire emotion tendency of netizens.

System and methods are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent or default connotation of individual terms for the linguistic structure containing such terms.

The invention discloses a part-of-speech-tagging-based dictionary construction method applied in shopping comment emotion analysis. The method comprises the steps of conducting pre-treatment on text data of a shopping comment, in other words, conducting segmentation and word segmentation on a comment text, filtering out words which are not used any more, and partitioning shopping domains; constructing a basic emotion dictionary and a network buzzword emotion dictionary; taking a shopping comment corpus as a data set, conducting part-of-speech tagging on the data set, extracting words with the part-of-speech as habitually used words, adverbs and adjectives as candidate words, selecting new emotion words as domain emotion words by calculating the PTF-IDF values of the candidate words, and adding the domain emotion words to a domain emotion dictionary. The domain emotion dictionary is combined with the basic emotion dictionary and the network buzzword emotion dictionary, emotional characteristic screening and extraction are conducted on the shopping comment, and the emotion classification of the shopping comment is studied. It is shown through experiments that the method is high in accuracy rate, free of limitation of shopping domains and more suitable for practical application.

The present invention is directed to a system for managing business knowledge expressed as statements, preferably sentences using a vocabulary, where such statements may be automated by the generation of programming language source code or computer program instructions. As such, the present invention also manages software design specifications that define, describe, or constrain the programming code it generates or programs with which it or the code it generates is to integrate. All information managed within the present invention is maintained within a relational database that is encapsulated within an object-oriented model. Each object in this model is subject to version control and administration using permissions. Each user of the system is an object and belongs to one or more groups. Users and groups may be granted privileges. Objects may be created, examined, used, modified, deleted, or otherwise operated upon only if corresponding permission or privilege has been granted. The vocabulary managed by the present invention consists of the function words commonly used in a language, such as the auxiliary verbs, prepositions, articles, conjunctions, and other essentially closed parts of speech in English, as well as open parts of speech, such as nouns, verbs, adjectives, and adverbs.

A system and method are provided for producing one or more unique account names in response to a user request, or in response to a user attempting to adopt another name that is unavailable. When performed in response to a user request, the method includes the steps of combining a randomly selected word element, such as an affix or adjective, and a randomly selected stem, such as a noun, to produce a random account name, and comparing the name with a list of existing account names to determine if it is unique. If so, the unique name is provided to the user for acceptance. Additional unique names can be produced by the same or a different method so that the user is presented with a plurality of unique names for consideration. For example, if the user attempts to adopt a name that is unavailable, a unique modified account name can be produced that is based on the name entered by the user. The modified name is produced by combining the requested name or a stem thereof with a randomly generated word element or a numerical seed to produce an alternate account name, comparing the name with the list of existing account names to determine if it is unique and, if so, providing it to the user for acceptance.

Embodiments generally relate to systems and methods for generating a sentiment dictionary and calculating sentiment scores of adjectives within the sentiment dictionary. A set of seed words can be identified and expanded using synonyms and antonyms of the set of seed words. Social media data can be parse to identify adjectives that link to the set of seed words with the words “and” or “but.” Matrices representing the attraction and repulsion among the linked adjectives can be generated. A factorization algorithm can be minimized to determine an output matrix that comprises positive and negative sentiment scores for each of the adjectives. In embodiments, a sentiment score for part of all of the social media data can be calculated using the output matrix, and one or more parts of the social media data can be classified as a positive or negative sentiment.

The invention relates to a structured natural language query and knowledge system, which allows a user lack of programming experience to input database for query or input rules in the form of structured language sentences. The range of the sentences is defined by improved object-related query languages for preference, object-related algebra, or both the object-related query languages and the object-related algebra. Conditions which appear in the form of the natural language are defined by corresponding form query texts, the user is prompted to use defined instructions and conditions for arranging and structuring natural language sentences, the instructions selected by the user and the parameters thereof are used as verb phrases of structured natural language sentences to appear, and the conditions selected by the user and the parameters thereof are used as adjective phrases to appear. The sentences are divided and changed to query texts in the form of translation used for database query and rule treatment.

A system, methods and user interface are disclosed for determining the connotation or sentiment type of a text unit comprising multiple terms and with a grammatical structure, such as subject+verb, verb+object, adjective+noun, noun+noun, noun+preposition+noun, and for highlighting or extracting such text units. The connotation or sentiment type of the text unit is determined by applying context rules where the context of the grammatical structure may change the inherent or default connotations of individual terms in the text unit. The methods provide a solution to the challenge of correctly or accurately determining the sentiment type of various linguistic structures under different context, and to the simplistic approach of using the inherent connotation of individual terms for the linguistic structure containing such terms, and highlighting only such terms without considering the contextual effects.

The invention discloses a video attribute representation learning method, which comprises the following steps of collecting a batch of data for training and testing of an automatic description algorithm of video text, wherein the data demand that each video corresponds to a few of sentences of corresponding text description; defining all nouns, verbs and adjectives appearing in the text description content in a training set as attribute labeling information of corresponding videos, wherein each video in the training set corresponds to a plurality of attribute tags; and representing a segment of video sequence as a single image, thereby transforming a complicated and difficult video sequence multi-classification problem into a simple single-image multi-label classification problem. The invention further discloses a method for automatically generating video text description on the basis of the video attribute representation learning method. The video attribute representation learning method has the advantages that efficient attribute characteristic representation of extracted videos is provided, by adopting a fusion method disclosed by the invention, the intact method for automatically generating the text description capable of reflecting semantic information of video attributes can be obtained.

The invention provides an English composition grammatical mistake correction method based on rules. According to the method, an English composition grammatical mistake correction model composed of an English composition preprocessing module, a rule grammatical mistake correction processing module and a grammatical mistake correction result generating module which are sequentially connected is included. After an English composition is processed through the correction model, finally article mistakes, adjective phrase mistakes, prepositional phrase mistakes, pronoun mistakes, verb tense mistakes, verb voice mistakes, irregular verb mistakes, auxiliary verb and modal verb mistakes, subject-verb disagreement mistakes, singular and plural disagreement mistakes, set structure mistakes, conjunction mistakes, word class confusion mistakes, word reuse mistakes, punctuation mark mistakes, abbreviation mistakes and sentence initial case-sensitive mistakes in the English composition can be corrected. The problem that an English composition grammatical mistake statistics correction method is not high in mistake correction precision and has fewer mistake correction types is solved.

The invention provides a method for extracting an attribution and a comment word with a template based on internet, which comprises the steps of: memorizing an attribute template aiming at a concept, the classification of which is manually labeled, by a machine readable dictionary; checking the evaluation index of a classification algorithm, selecting the maximum entropy, and ensuring a PMI value and an attribution word when training a classification model; extracting an original attribution set by collocating a template based on the internet, filtering the attribution based on a classification rule, expanding an attribution set with a connecting phrase template based on the assumption of Resnik, filtering again to form a process of cyclic iteration, evaluating the performance of the attribution extracting method according to the precision, the recall ratio and the comprehensive index F to obtain a relationship curve graph of the precision and the recall ratio; and extracting an individal comment word to the product attribution based on the product attribution extracted by the internet to form an effective attribution-evaluation pair, judging good evaluation and bad evaluation according to the word characteristic of an evaluation adjective in evaluation information, and generating a market feedback comprehensive value.

A method for automatically analyzing the text of a document to generate verification questions to be administered to a user as a quiz for the purpose of verifying whether the user has read the document. Syntactic analysis is applied to statements (e.g. sentences) in the text to automatically generate various types of verification questions, including fill-in-the-blank, true / false, and multiple-choice questions. Nouns and proper nouns in a statement may be used to generate fill-in-the-blank questions; numerical values may be used to generate fill-in-the-blank, true / false and multiple-choice questions; and verbs, adjectives and adverbs may be used to generate true / false questions. The questions may be generated dynamically for each user, or generated once, stored and used for multiple users.

What is disclosed is a system and method for dynamically reducing the number of choices by reordering the selectable menu options in each menu of a color adjustment tool based on image content, selections in other menus, and usage history. Color names and color modifiers are reduced and / or reordered through image analysis, with most frequently occurring colors being placed at the top of the menu and excluding less frequently used or unused colors from the menu. Adjustment adjectives are reduced by eliminating nonsensical or rare color adjustment combinations (e.g. make the grays much more colorful, make the blues yellower), and / or reordered based on usage history, either by the individual user or by aggregating over many users.

A keyword adjective is used to identify a URL or address within script included in a markup language document. A Web page, or hypertext markup language document that includes script cannot readily be parsed to identify the URL or address. The present invention includes a predefined identifier as a keyword adjective immediately preceding the string comprising the URL or address referenced within script conforming to the European Computer Manufacturers Association (ECMA) specification. Use of the keyword adjective in this manner facilitates identification of the URL or address. Once thus identified, the URL or address can be modified to fix a broken link. This approach can also be used more generally to identify other entities (other than an address) for an object referenced in the script.

Single stroke text entry via a telephone keypad is subject to ambiguities resulting from the overloading of three letters on one key. After text is entered the three letter per position code block represented by the key strokes for a word position is hashed to all matches in a stored dictionary type word list. The resulting word group of alternative word choices for that word position is subjected to probability analysis. Probabilities of usage of specific words are evaluated based on frequency of usage in the selected language, such as English. Syntax type probabilities of word sequencing are evaluated through (i) rules based on transitional probability of use of two particular words in sequence in English usage and (ii) rules based on probability of relative positioning of words of particular word categories (e.g., nouns and adjectives) in a sentence structure in English usage. A word trellis or lattice represents choice paths for alternative sentence structures. By selecting the path with the highest probability values, highly accurate sentence reconstruction is provided. In addition to use in the telephone keypad text entry context, described systems and methods are also applicable to a variety of word processing and other systems wherein computer stored text is subject to ambiguities as to intended words.

The present invention discloses a method for concluding and classifying online comments of a hospital, and aims to conclude various online evaluations of the hospital by patients, summarize the overall impression of the hospital, and implementing classification of the comments. The method comprises the following steps of first dividing crawled Chinese comment content into a plurality of short sentences by using regular expression; then performing word segmentation and part-of-speech tagging of each short sentence, and merging adjacent nouns into a noun; replacing adjectives on basis of synonym dictionaries with the principle that low-frequency words are replaced by high-frequency words; storing the obtained noun+adjective phrases into a database, and simultaneously establishing mapping relation among the phrases, the short sentences and the comments; and inputting the tile of the hospital, and selecting a plurality of high-frequency phrases from the database as the overall evaluation of the hospital. According to the method, the online comments of the hospital can be simplified, the trouble of reading various comments is saved, and the comments can be read by classification conveniently, thereby facilitating healthcare service choice and hospital choice.

The present invention, in one embodiment, aids the user during composition of emails / letters / documents with assistance for correct gender usage. In one example application, first an automated user information look-up process is initiated over centralized databases using the proper names mentioned in the composition. Once matches are found, gender-related information is retrieved and the composer is assisted with gender recognition tools while composing gender-sensitive statements. When mismatches between proper nouns and the corresponding adjectives / pronouns are found, this method proceeds with highlighting or otherwise flagging the mismatching words. Upon right-clicking the highlighted words, the user is given suggestions for the most probably correct options. Examples of the idea explained in this invention can be incorporated in existing software / systems of email / document editor / composers.