245 results about "Encyclopedia" patented technology

Methods, systems and computer programs for automatic, highly accurate machine comprehension of a plurality of segments of free form unstructured text in a natural language. The system answers a plurality of complex, free-form questions asked in a natural language, based on the totality of input text. The system further uses a multi-dimensional data model to measure the total effects of actions/verbs acting on various unique nouns present in the input text. The system may convert the questions into another multi-dimensional data model and may then compare the two data models in program memory to derive the answers to the posed questions. The system may then automatically detect unknown words and optionally look them up in digital information sources, such as online dictionaries and encyclopedias, to fill in the gaps in knowledge to answer the questions with expert-like reliability.

The present invention relates to a semi-automatic construction method for knowledge base of an encyclopedia question answering system, in which concept-oriented systematic templates are designed and important fact information related to entries is automatically extracted from summary information and body of the encyclopedia to semi-automatically construct the knowledge base of the encyclopedia question answering system. A semi-automatic construction method for knowledge base of an encyclopedia question answering system of the present invention comprises the steps of: (a) designing structure of the knowledge base with a plurality of templates for each entry and a plurality attributes related to each of the templates; (b) extracting structured information including the entry, an attribute name and attribute values from summary information of the encyclopedia; (c) extracting unstructured information including an attribute name and attribute values of the entry from a body of the encyclopedia; and (d) storing the structured information and the unstructured information in corresponding template and attribute of the knowledge base according to the entry.

An online video search system, including a tag discoverer including a web encyclopedia crawler for (i) accessing a web encyclopedia to find web pages related to at least one designated reference topic, and (ii) retrieving a plurality of web pages by performing an n-level depth recursive traversal of the web pages found, and web pages that are hyper-linked thereto, a concept extractor for extracting important concepts founds in the retrieved plurality of web pages, and a user interface for providing at least of the important concepts extracted by the web page processor to an online video search engine. A method and a computer-readable storage medium are also described and claimed.

The invention provides a deep question and answer method, which comprises the following steps of: 1, receiving question data; 2, carrying out a first retrieval in a knowledge base database, wherein the knowledge base database comprises factual information in encyclopedia; and 3, carrying out a third retrieval in a self-defining data set, wherein the third step comprises the steps of: 3.1, classifying the questions by a machine study method on the basis of a sentence pattern model set, and determining the sentence pattern mode of questions; and 3.2, obtaining second type keywords through the questions matched with the sentence pattern mode, and retrieving the self-defining data set through the second type keywords. Corresponding to the method, the invention also provides a medical retrieval system which comprises an input module, a first retrieval module and a third retrieval module, wherein the first retrieval module is used for retrieving the knowledge base database, the knowledge base database comprises the factual information in encyclopedia, and the third retrieval module is used for retrieving the self-defining data set.

The invention relates to a method for constructing a knowledge graph based on entity extraction and relationship mining of a rule model. The method comprises the following steps: step 1: crawling data of an encyclopedia knowledge base of a target region, and defining dictionaries of foods, pesticides, nutrition and plant diseases and insect pests, so as to be convenient for rule mining; step 2: carrying out HTML (Hypertext Markup Language) label removal on encyclopedia type data to obtain Chinese texts and obtaining a URL (Uniform Resource Locator) link, so as to be convenient for subsequent processing; step 3: obtaining more complete entity attribute information by adding manually annotated relation attribute information; and step 4: obtaining an event and establishing a graph relation. According to the method provided by the invention, text information is converted into word vector mathematical information; vector similarity comparison is carried out and a relation between entities is labeled according to a relation between numbers, so as to represent a core knowledge base for the field and improve and optimize search quality; and a process from a simple character string to entity comprehending is realized.

The invention provides a building method of a knowledge map based on a vertical field. The method comprises the following steps of (1) extracting the word realization of classes of an on-line encyclopedia and the hyponymy between classes; (2) merging the field knowledge information, defining the data attribute and the relationship attribute of the field, and further setting the statute on the definition domain and the value domain of the attributes; (3) studying an entity layer, i.e., extracting an entity and filling the attribute value of the entity; performing mass processing on structurized and semi-structurized data by D2R or data collecting tools; and for non-structurized text data, defining the classes and the attributes of the upper layer body and the relationship between the classes and the attributes, and recognizing examples according to the relationship between the classes and the attributes. The method has the advantages that by using the method, the built knowledge classification of the vertical field knowledge map is clear; the self study and the automatic expansion of the knowledge map are realized; and the key effects are achieved on the information retrieval and semantic analysis of the vertical field.

The invention concerns a method of creation, maintenance, and peer-review of web-based collectively written encyclopedia. The invention combines the mechanism of Wiki-style collaborative environment, which allows users to modify articles, with the principles of peer-reviewed encyclopedias, in which articles are approved (i.e., endorsed) by experts. In the preferred embodiment, each article has a curator or curators who are responsible for the article content. Each article can be modified by users, but the modification is hidden from the general public until it is evaluated and approved by the curators. The encyclopedia stores the history of all revisions and evaluations. If the curators fail to evaluate the modification within a certain predefined period of time, the curatorship of the article is offered to the person who made useful modifications to the article (according to the history of evaluations). This method ensures that each article has a curator who maintains its content in a timely manner.

The invention discloses a webpage information extraction method, in particular a method for extracting concept attributes from a network encyclopedia data source and processing the concept attributes. The method comprises the following steps of: constructing an example list, and extracting candidate attributes of examples in the list from a multi-source heterogeneous data source; performing synonymic induction on the extracted attributes, and putting synonymic attributes in the same set; sub-classifying the induced attributes; analyzing the corresponding attribute value types of the classified attributes; and recommending the attributes and corresponding attribute value type information to a user, or storing the attributes and the corresponding attribute value type information into a structured database. By adoption of the scheme of the invention, high-quality concept attribute information can be extracted from a webpage, a knowledge base can be better constructed, and other natural language processing tasks such as extraction of attribute values, text classification and classification of query logs in a search engine can be better performed.

The invention discloses a method for answering with natural language, which is used for instantly and effectively answering the questions of users. The method comprises the following steps of: (1) performing question analysis on a question input by a user; (2) answering the question by use of the question analysis result and the corpus of community questions and answers; (3) answering the question by use of the question analysis result and the encyclopedia corpus; and (4) verifying and selecting the answers returned by the steps (2) and (3), and finally returning the best answer to the user.

The invention discloses a knowledge map-based Chinese tourism domain knowledge service platform construction method. The method comprises the steps of obtaining structured tourism knowledge from an existing Chinese encyclopedia knowledge base, fusing the knowledge and crawling tourism website page data; performing knowledge completion on the Infobox attributes of the entity through a self-definedattribute matching rule; using a Stanford ontology modeling tool Protege to construct a tourism domain ontology, and combining D2RQ with the constructed tourism domain ontology to convert data into anRDF triple format to obtain a tourism domain knowledge graph and a Neo4j graph database storage task of a tourism knowledge base; wherein the knowledge fusion task comprises the steps of calculatingsemantic similarity between entities by using an improved deep learning knowledge representation model BERT to complete entity alignment, performing attribute fusion based on a principle and a statistical method, and performing a triple fusion subtask by adopting a majority voting algorithm. According to the invention, tourists can obtain one-stop comprehensive services conveniently.

Mined semantic analysis techniques (MSA) include generating a first subset of concepts, from a NL corpus, that are latently associated with an NL candidate term based on (i) a second subset of concepts from the corpus that are explicitly or implicitly associated with the candidate term and (ii) a set of concept association rules. The concept association rules are mined from a transaction dictionary constructed from the corpus and defining discovered latent associations between corpus concepts. A concept space of the candidate term includes at least portions of both the first and second subset of concepts, and includes indications of relationships between latently-associated concepts and the explicitly/implicitly-associated concepts from which the latently-associated concepts were derived. Measures of relatedness between candidate terms are deterministically determined based on their respective concept spaces. Example corpora include digital corpora such as encyclopedias, journals, intellectual property datasets, health-care related datasets/records, financial-sector related datasets/records, etc.

The invention relates to a system suitable for a blind person to surf the Internet, comprising an automatic server news downloading system and a client application system. A server system can realize real-time news downloading, store the news into a server and realizes real-time updating; and a client system can correspondingly respond to voice input of the blind person by virtue of voice recognition and synthesis and outputs a voice. For special case of the blind person, the system realizes three core functions of the Internet, namely information acquisition, knowledge learning and interaction. By applying the system provided by the invention, the blind person can effectively listen to news by virtue of the Internet, listen to an electronic books, inquire encyclopedia nouns and report and listen to a post, wherein the news listening system can support the blind person to sequentially listen to news in programs, and the blind person can pay close attention to interested news by keyword search and related news search.

The invention relates to a field entity attribute relation extraction method based on distance supervision, belonging to the technical field of natural language processing and depth learning. The method inlcudes constructing a domain knowledge base of Chinese tourist attractions, through the Chinese encyclopedia website and tourism website to obtain a large number of tourism domain text collections, using the constructed tourism domain knowledge base of entity pairs to obtain the relational instance text collections from the tourism domain text collection; using the theme model keyword similarity calculation and keyword pattern matching to denoise; finally, using the training corpus which is composed of positive and negative data under each relationship, the part-of-speech feature, dependency feature and short syntax tree feature of the training corpus are extracted, and the three features are fused into a larger feature with more abundant semantic information, and then the relationship extraction model is trained. Experiments show that the F value of the fusion of the three features extracted from the de-noising training corpus is the highest and the extraction performance is thebest.

The invention belongs to the technical field of open knowledge extraction and specifically relates to a field encyclopedia establishment system based on general encyclopedia websites. The system is divided into a plurality of modules, namely an encyclopedia data crawling module, an encyclopedia data preprocessing module, a related entity searching and ranking module and an entity clustering module. The field encyclopedia establishment system based on the general encyclopedia websites has the following beneficial effects: the field encyclopedia is mostly established manually at present, which takes time and labor, and as all related entities cannot be found out manually, the coverage rate is low; instead, the field encyclopedia is established on the basis of the field related entities found out by the field encyclopedia establishment system, and in this way, the labor of establishing the field encyclopedia can be greatly reduced and the coverage rate can be greatly increased; meanwhile, the field encyclopedia established by the field encyclopedia establishment system is greatly convenient for users to obtain the knowledge in specified fields; complex searching and screening processes are omitted, and the pattern that a user passively searches for information is changed into the pattern that the system initiatively provides information.

The invention relates to a method and a system based on encyclopedia data for classifying entities. The method comprises the following steps of analyzing items of the entities in the encyclopedia data to obtain a descriptive attribute set corresponding to the entities; extracting categories set in the encyclopedia data and an attribute template set corresponding to the categories; determining the categories of the entities and classifying the entities based on the similarity of the descriptive attribute set and the attribute template set. According to the method, the descriptive attribute set in the encyclopedia data is compared with the preset attribute template set, the entities are classified, the data of which the similarity is lower than a threshold value are clustered, and thus the purpose of classifying the data is realized.

The invention discloses a multi-data source oriented network data collection and presentation method. Based on the research of data collection strategies of six media platforms, such as Sina Weibo, People's Daily, Baidu Encyclopedia, Baidu Tieba, WeChat Public Homepage and Dongfang Wealth Stock Bar, the method adopts Servlet background scheduling technology to integrate the web crawler oriented tomulti-data sources, and solves the data collection problem of different media platforms. In this implementation, Firstly, the manual operation such as simulated login is realized by means of Web application test kit Selenium. Secondly, the Xpath element query technology is used to analyze the source code of the web page, and the data information is extracted and stored in the database. Finally, the crawled data is read out from the database and displayed on the front-end page. Experiments show that the crawler achieves the maximum collection efficiency on the premise of ensuring data integrity.

The present invention discloses a Chinese integrated entity linking method based on a graph model. An ambiguous entity in a text can be mapped into a specific entity in a real world, in order to provide aid for knowledge base expansion, information extraction and search engines. The method mainly comprises three parts of generating a candidate entity, constructing an entity indicator diagram, and disambiguating an integrated entity. For a given text, an entity referent item therein is recognized to obtain the candidate entity. The entity referent item and the candidate entity thereof are regarded as graph nodes to construct an entity referent graph. An in-degree and out-degree algorithm is applied to the entity indicator diagram for implementing disambiguation of multiple ambiguous entities in the text. The present invention does not depend on the knowledge base completely in the establishment of the entity indicator diagram, and also can implement incremental evidence mining to find evidence on an encyclopedia webpage. Dependence path analysis is employed to find the possibly related entity referent item. When the dependence path sizes of two entity referent items are within a set range, the two entity referent items are regarded as the possibly related entity referent items. Further, whether their candidate entities have relations in the real world is determined, so that the efficiency of disambiguation is greatly improved.

The invention relates to a Chinese word similarity calculation method based on a fusion strategy. The method comprises steps of calculating word similarity based on the combination of four of HowNet,synonym forest, Word2Vec trained Chinese Wikipedia encyclopedia corpus and a Baidu dictionary; for two input words, firstly, judging whether the synonyms exist in a HowNet or synonym forest or not; ifyes, using the HowNet or synonym forest for calculating the similarity, if not, judging whether the HowNet or synonym forest exists in the Wikipedia corpus or the Baidu dictionary or not, and if yes,using the Word2vec or the Baidu dictionary for calculating the similarity of the words. The invention provides a Chinese word similarity calculation method based on a fusion strategy. According to the fusion strategy, the known network, the synonym forest, the word2vec and the Baidu dictionary are comprehensively considered, advantage complementation among strategies is formed, the calculated Spearman correlation coefficient and Pearson correlation coefficient are higher than those of other methods, the accuracy of a word similarity calculation result is improved, and the requirements of practical application can be well met.

The invention discloses a word2vec-based remotely supervised non-taxonomic relation extraction method and system, which can extract non-taxonomic relations in the field of vegetables. The method comprises the steps of crawling network vegetable field non-structured text data of a network encyclopedia and a large vegetable website to serve as corpora, and preprocessing the corpora in sequence to obtain primary training corpora; and training a word2vec model by utilizing the primary training corpora, and obtaining a spatial vector of each sentence by utilizing the word2vec model; aggregating the primary training corpora according to the types of the non-taxonomic relations, and for aggregated data of each relation, extracting a common sentence mode and an uncommon sentence mode; selecting two sentence spatial vectors accordant with two different modes as initial centers of a k-means clustering method, clustering all sentence spatial vectors, selecting a category accordant with the common sentence mode, and obtaining the training corpora with relatively high quality; and training a convolutional neural network model by the training corpora with relatively high quality, and through a fully connected softmax layer, extracting the non-taxonomic relations.

The invention discloses a method for automatically establishing back-of-book indexes of a book based on book contents. The method comprises the following steps: first, analyzing text in a digital book; taking a chapter as a unit, and performing part-of-speech tagging on the text by using a natural language processing tool to obtain a part-of-speech array; matching by utilizing a high-frequency part-of-speech rule, and extracting candidate phrases; then, classifying to obtain the phrases to serve as candidate index terms by using a support vector machine algorithm by utilizing semantic and grammatical characteristics; calculating the similarity between the candidate index terms and the field corresponding to the book to serve as termhood; calculating information amounts, term frequency, point mutual information and encyclopedia key values to obtain an index degree; calculating a title offset distance, a candidate index term proportion and interestingness to obtain a context weight value; finally, combining the termhood, the indexing degree and the context weight value to obtain an index score, and obtaining the book index terms through limited sequencing. According to the method, the indexes can be added to the book which does not have the back-of-book terms, and the readability and the searchability of the book are improved.