45 results about "Metasearch engine" patented technology

A computer implemented meta search engine and search method. In accordance with this method, a query is forwarded to one or more third party search engines, and the responses from the third party search engine or engines are parsed in order to extract information regarding the documents matching the query. The full text of the documents matching the query are downloaded, and the query terms in the documents are located. The text surrounding the query terms are extracted, and that text is displayed.

A system and method for performing domain-specific knowledge based metasearches. A metasearch engine is provided for accessing a searching text-based documents using generic search engines while simultaneously being able to access publication based databases and sequence databases as well as in-house proprietary databases and any database capable of being interfaced with a web interface so as to produce search results in text format. A data mining module is also provided for organizing raw data obtained by unsupervised clustering, simple relevance ranking, and categorization, all of which are done independently of one another. The system is capable of storing previous search data for use in query refinement or subsequent searches based upon the stored data. A search results collection browser may be provided for analyzing current browsing patterns of the user for developing weighting factors to be used in ordering the results of future searches.

A user of a meta-search engine submits a query formulated with operators defining relationships between keywords. Information sources are selected for interrogation by the user or by the meta-search engine. If necessary, the query is translated for each selected source to adapt the operators of the query to a form accepted by that source. The query is submitted to each selected source and answers are retrieved from each source as a summary of each document found that satisfies the query. The answers are post-filtered from each source to determine if the answers satisfy the originally formulated query. Answers that satisfy the query are displayed as a list of selectable document summaries. The analysis includes computing a subsumption ratio of filtered answers to answers received that satisfy a translated query. The subsumption ratio is used to improve the accuracy of subsequent queries submitted by the user to the meta-search engine.

Systems, methods and computer readable media for performing a domain-specific metasearch, and obtaining search results therefrom. A metasearch engine capable of accessing generic, web-based search engines and domain-relevant search engines is provided to receive one or more queries inputted by a user, and to search for documents on at least one the generic, web-based search engines and domain-relevant search engines which are relevant to the queries. Raw data search results are fetched in the form of text documents. Relevant data including semantic information are extracted from the raw data search results, and converted to a local format. The relevant data having been converted to the local format may be visualized as a network visualization. Additionally or alternatively, the raw data search results may be ranked and/or filtered based on the linking of the relevant data. Visualization of the raw data having been ranked and/or filtered may be performed in addition to, or alternative to visualization of the network.

A meta search engine (1) receives a query (q_T) from a user (U), and submits adapted queries (q₁-q_n) to n search engines (S₁-S_n). The results (R₁-R_n) are adapted (R₁′-R_n′) and combined to provide a result set R′. In parallel, the meta search engine (1) accesses a selected hit matrix (H) populated with values for correspondence of queries q₁-q_m with web pages p_i-p_n. These values are the number of “hits” for pervious searches. The pages (R″) retrieved from a row for q_T are combined with the search engine (S₁-S_n) results to provide a final result but which is ranked according to previous search experience. The hit matrix may be dynamically selected according to a user community. The query (q_T) need not exactly match a hit matrix query (q₁-q_n) as rows can be selected according to similarity to the current query q_T with weightings applied.

A search enhancement system (whether linked through an API to a search engine or integral to a search engine) creates a series of different narrow searches through the selective use of synonyms, hyponyms for a narrower search, hypernyms for a broader search, and antonyms for a reverse search. Lexical analysis can also be used to create alternative narrow searches. This allows a user to explore different nuances of meaning in an original search phrase until the user finds what he or she wants, while keeping individual searches narrow, thus leading to more focused search results.

The invention discloses a meta-search engine personalizing method based on Agent. The method includes the steps of firstly, judging whether a user uses a meta-search engine for the first time or not, if so, moving to the second step, and if not, moving the sixth step; secondly, digging browsing records of the user; thirdly, initializing user interest models; fourthly, grouping the user; fifthly, acquiring group interests; sixthly, for the user does not use the meta-search engine for the first time, judging whether the user needs to search information or not, if so, moving to the seventh step, and if not moving to the tenth step; seventhly, recommending related information; eighthly, recording links clicked by the user; ninthly, updating user interests; tenthly, finishing. The method applicable to the meta-search engine of Internet has the advantages that the user is grouped and related recommendation is provided according to interests of the user, and the user can obtain targeted search results.

The present invention is applicable to the field of network information processing and provides a field subject-oriented Web news dynamic aggregation method. The method comprises the following steps of: for a field site list pre-defined by a user, according to a subject provided by the user, acquiring a search record list by utilizing a vertical search engine and a meta search engine; performing deduplication on the search record list and identifying a Web news webpage to obtain a news webpage search record list; with a Web information extraction method, acquiring a structured news list from the news webpage search record list; and performing ranking on the structured news list according to a field model to obtain an ordered structured news list, and returning the ordered structured news list to the user as a dynamic aggregation result. According to the field subject-oriented Web news dynamic aggregation method, a multi-source associated Web news set is acquired in real time according to a field and a subject provided by the user, an interactive mechanism where the ranking of the Web news depends on the popularity of the Web news is provided, and the purpose is to provide a convenient and efficient internet information acquisition and sharing mode.

The invention discloses a Meta search engine ranking method and a Meta search engine, which is used for solves the problem that the search results obtained from the Meta search engine by a user are inaccurate in the prior art. The method comprises the following steps: the Meta search engine extracts a search keyword according to a search request input by the user to determine the text type corresponding to the search keyword; the Meta search engine sends the search keyword to each called independent search engine; the Meta search engine receives the search result returned by each search engine and determines the ranking of each search result according to the saved weighting coefficient of the text type corresponding to each independent search engine; the search results the rankings of which are determined are provided for the user. The scheme can provide the user with the more accurate search results and greatly increases the search quality of the search results provided by the Meta search engine.

The invention discloses a search method for a meta search engine, comprising the following steps: building a user interest model according to a webpage browsed by the user; dispatching a member search engine according to the query requirement of the user and an interest model of the user; and according to the correlation degree of a query result and the user interest, fusing and sorting the result. The invention also provides a search device for a meta search engine. The method is a query result fusion method based on the user interest. By considering the user interest and the correlation degree of the user interest and the member search engine, the accuracy of the search engine can be improved without affecting the normal browsing process of the user.

The invention discloses an Agent-based intelligent meta search engine system. The system comprises a user personalized Agent, a mobile Agent, a scheduling management Agent, a retrieval and synthesis Agent, and a public interest blackboard, wherein the user personalized Agent is used for studying user retrieval interest knowledge, and supports personalized and group pushing service; the mobile Agent is used for excavating the client records, interacting with the user personalized Agent, and updating the user interest knowledge; the scheduling management Agent is used for generating a personalized scheduling strategy; and the retrieval and synthesis Agent interacts with the scheduling management Agent and the user personalized Agent to provide a personalized search result for the user. The Agent-based intelligent meta search engine system provided by the invention can realize intelligent searching, scheduling and result synthesis of the meta search engine based on the autonomy, study characteristics and interoperability of the Agents, and has the advantages of high search coverage rate, personalization and high intelligent degree.

A method is disclosed for a search engine or part of a search engine which utilizes collective intelligence, evaluation, and judgment, including web intelligence, to create and adapt the content of a generalized index hierarchy for digital resources to be searched. Digital resources to be searched can be stored and managed as a localized or distributed repository of images, video, audio, graphical or other multimedia data objects, as well as structured composite items, services, programs, modules, files, documents, systems, applications, networked peers, and agents, which may be difficult or costly to be indexed. In particular embodiments the claimed invention focuses on the indexing of semantic contents and/or pragmatic characteristics of such digital resources. By tracking and analyzing the searching behavior of users, proxies, and/or meta-search-engines, a search index can be created, tuned, improved and optimized. The claimed method in certain embodiments also incorporates an adaptive and evolution mechanism which allows relevant digital resources that may otherwise be overlooked to be found. The claimed invention can be applied to databases, web searching, personal/local search, community search, and broad-based or vertical search engines for internet, intranet, extranet or other uses.

The invention discloses a duplication elimination method based on search results of a metasearch engine. The duplication elimination method based on the search results of the metasearch engine is provided to solve the problems that in the prior art, duplication elimination cannot be carried out on the same web pages of URLs with different formats and redirected web pages, and sentences and articles cannot be represented fully according to information around punctuation marks, positions of the punctuation marks and fuzzy matching of word frequencies. The method comprises following steps such as 1, judging whether there are duplicated web pages or not according to URL addresses; 2, computing the title similarity of the two web pages and the abstract similarity of the two web pages; 3, computing the similarity of the web pages according to the title similarity and the abstract similarity; and 4, determining that the two web pages are duplicated if a similarity value Sim (A, B) is more than a threshold. The method can be applied to the field of duplication elimination based on the search results of the metasearch engine.

The invention discloses a label automatic generation method based on a meta-search engine. The method comprises the steps that firstly, text preprocessing optimization is conducted, Chinese word segmentation is conducted and meanwhile, basis information of words is saved and the basic information comprises part of speech, word position, word frequency of which quintuple is composed; secondly, the words are filtered, stop words are removed, part of speech filtration is conducted, and according to experience, noun, verb and gerund are kept and noise disturbance is reduced; word information quantity is recalculated again, by counting the word basic information, word position score, word frequency and word span are calculated and comprehensive score is calculated as weight of the words; finally, the similarity between words is calculated as edge weight in TextRank algorithm and the TextRank algorithm is used for calculating TextRank value of each word. According to the label automatic generation method based on the meta-search engine, the meta-search engine technology and automatic generation label are used, the automatic label technology is applied to the search engine and therefore recall ratio and precision ratio are guaranteed.

The invention discloses a method for merging and ranking retrieval results for academic meta search. By the aid of the method, problems that existing search engines are low in coverage rate and computation and convergence speed, incomplete retrieval results are obtained by the existing search engines and importance is not attached to paper in novel fields mainly can be solved. The implementation scheme includes that the method comprises 1), invoking component engines to retrieve documents; 2), computing the capacity of search engines by the aid of proportions of results of the component search engines; 3), comprehensively considering publication years of literature, influence factors of literature publication periodicals or holding times of publication conferences, quoted times of the literature and the relevance of the literature, combining the publication years of the literature, the influence factors of the literature publication periodicals or the holding times of the publication conferences, the quoted times of the literature and the relevance of the literature with the difference between the retrieval capacity of the component search engines and computing weights of the retrieved documents; 4), eliminating duplication of the results fed by the component search engines, merging the results and displaying the retrieval results. The method has the advantages that the importance of the literature in the new fields can be improved while the comprehensive and accurate retrieval results are provided for users, accordingly, the efficient retrieval experience can be provided for the users by the academic meta search engines, and the method can be applied to internet information retrieval and digital libraries.

The invention discloses a method and a device for acquiring network information. The method comprises the following steps of: executing a preset search task, and searching for network information relevant with pre-inputted keywords by utilizing a meta search engine; and grading the value of the network information according to a preset filter rule and the relevance of the contents of the searched network information, and saving value grades to reach the network information of a first score threshold value. By the method, new search engines can be prevented from being compiled artificially, and the more comprehensive information can be searched for by the existing search engine, so the efficiency of acquiring the network information is improved obviously, the searching flexibility is improved effectively, and accuracy of search results is ensured to the great extent.

The present invention discloses a group division-based meta-search engine personalized result recommendation method. The method includes a first step of determining whether a meta-search engine is used for the first time, if yes, executing a second step, if not, executing a fourth step; the second step of constructing a user model; a third step of dividing users into groups; the fourth step of determining whether information needs to be searched, if yes, executing a fifth step, if not, executing a tenth step; the fifth step of acquiring a search result list; a sixth step of determining whether a user belongs to the user group, if yes, executing a seventh step, and if not, executing an eighth step; the seventh step of recommending search results; the eighth step of recording clicked search results; a ninth step of updating the user model; and the tenth step of terminating. According to the method, the user model is constructed for the user in meta-search, and the users are clustered and divided into groups, so that personalized search results are recommended to the users.

The invention discloses a personalized meta-search engine searched result merging and sorting method. The method is realized through the following steps: (1) establishing user system interests; (2) searching documents by search engines; (3) merging result documents of member search engines; (4) dividing interest categories of the result documents; (5) obtaining personalized sorting weights; (6) displaying search results; and (7) updating the user system interests. According to the method, the number of the member search engines, the sum of the member search engine results, the number of same result documents and the position information of result documents in each member search engine are considered at the same time, and the influences, from the user interests with different personalization degrees, on the result sorting is combined, so as to realize the more correct and more efficient user personalized search experience of meta-search engines.