233 results about "Vertical search" patented technology

An embodiment of the current invention is directed to presenting a preview of search results for a suggested search. A search engine query is received. One or more search results are generated. One or more suggested, search terms are generated. A search engine results page is generated, including the one or more search results and the one or more suggested, search terms. An indication is received, indicating that a preview of search results related to a selected, suggested, search term is to be displayed. A preview window including a results section and a menu-bar section is generated. One or more search results related to the selected, suggested, search term are acquired. The one or more search results are presented in the preview window. The preview window allows interaction with the one or more search results.

A vertical search engine may rank items based on both the quality of data associated with each item and the popularity of each item. The vertical search engine may access data associated with items from a variety of different sources, including feed sources and crawl sources. Data quality inputs are determined for each item based on the quality of the data associated with each respective item. In addition, popularity inputs are determined for each item based on user interest in each respective item. A global rankings score is then calculated for each item based on the data quality inputs and popularity inputs for each respective item. The global ranking score may be used to order search results for search queries in such a way that items from feed data and items from crawl data may be displayed in a unified manner, rather than being segregated by data source.

The invention is suitable for the internet information processing field and provides an internet web page cleaning method, an internet web page cleaning system and an internet web page cleaning device. The method comprises the following steps that: an inputted web page is analyzed; the label content of the web page is automatically corrected; a document object model tree is established; block element nodes of HTML provided with representation content in the document object model tree is maintained, and a structural block tree corresponding to the document object model tree is generated; the inputted web page is classified according to the defined web page type on the basis of the structural block tree; semantic block analysis of the web page is performed according to the web type to which the web page belongs, and important blocks and text information of the important blocks are extracted and outputted. The internet web page cleaning method can realize cleaning of any web page, has high cleaning accuracy and can be applied in aspects like browsing of mobile terminals, a search engine, subject-oriented information acquisition, automatic information extraction, vertical search and so on.

A method for characterizing image contents automatically or semi-automatically using image acquisition parameters and metadata is presented. The method establishes probabilistic and deterministic relationships between different types of metadata and the semantic attributes and contents of images. It furnishes a mechanism that enables the automatic and semi-automatic classification, annotation, tagging, indexing, searching, identification or retrieval of images based on their contents, semantic properties and metadata characteristics. The method uses, but is not limited to, image capture metadata such as focal length, exposure time, relative aperture, flash information, ISO setting, angle of view, subject distance, timestamp, GPS information as well as other forms of metadata, including but not limited to, captions, keywords, headings, tags, comments, remarks, titles which may be automatically, semi-automatically, or manually generated. The present invention can be applied to image databases, web searching, personal search, community search, broad-based or vertical search engines for internet, intranet, extranet or other usages.

The invention discloses a vertical search engine and a method for searching contrast association shopping information. The search engine consists of data crawling module, a web page resolution module, an index memory module, and a retrieval module. With the adoption of the method, when a user queries some electronic product, a search server can return attribute information of the product to the user on different shopping platforms; the attribute information mainly comprises prices, evaluations and sales trends in the different shopping platforms; the contrast association shopping information can be queried; the user can contrast to purchase and preferentially select the product conveniently; and the attribute information of related products can be checked in all aspects.

A graphical user interface stored in a memory of a client computer is provided. The interface comprises a prompt field for a vertical search query from a user. The interface further comprises a field for displaying a plurality of names. Each such name represents a vertical collection. The plurality of names is automatically populated, at a time when the user is still entering characters in the prompt field, as a function of one or more character strings in the prompt field. A computer comprising a memory storing instructions for receiving a vertical search query, communicating the query to a remote computer, and receiving a plurality of names from the remote computer. Each name represents a vertical collection having relevance to the vertical search query. The plurality of names is displayed at a time when the user is still entering additional characters into the vertical search query.

The present invention relates to a self-service intelligent vertical search method and includes the following steps: cookies files of users, registered information, historical search information and ordered attention module can be utilized to study preferences of users, and the preferences of the users are set as statistical models of the users which are real-timely stored to a database of a search engine dynamically. A final key word/words collection file can be obtained by studying high speed Chinese word segmentation and search habits of users. The search engine can search all the information that is relevant to the inertial key sentence/word through a network database. Meanwhile, the search results are matched with the statistical models of the users and the search results which fit for the preferences of the users can be returned to the users. The present invention has the beneficial effects that the users can find out the needed information from the huge information collection and study using preferences and habits of the users actively, and then the search results can cater to ''tastes'' of the users more and the users make judgment to the values of the search results totally.

The invention discloses an ordering system of comprehensive searching result and method in data treating domain, which comprises the following steps: A, inputting term to the comprehensive searching engine; searching; getting all vertical searching engine result; B, extracting data information from the data bank with the ordering module; adopting sort algorithm; calculating each comprehensive value of vertical searching engine in the searching result; C, comparing comprehensive value of each vertical searching engine; ordering for the vertical searching engine; displaying the final ordering information; outputting. This invention can enhance flexibility for comprehensive searching result, which can meet personalized demand of the users.

The embodiment of the invention discloses a method, a system and a device for querying a vertical search, wherein the method comprises the following steps: a query server acquires the query information of a user; the query server acquires a query result from a lookup dictionary of a commodity category server according to the query information, wherein the query result refers to the commodity sub-categories under the commodity category matched with the query information and corresponding weight of the commodity sub-categories; and the query server sorts the commodity sub-categories in the query result according to the corresponding weight thereof, and sends the obtained sort result to the user, so that the user looks up the commodity sub-categories, and a log server generates a log according to the commodity category looked up by the user and the query information, and sends the log to an analysis server to carry out statistical analysis and then obtain a statistical analysis result, wherein the statistical analysis result is used for updating the lookup dictionary of the commodity category server for subsequent query. Through the method, the system and the device provided by the embodiment of the invention, the query result returned to the user according to the click records of the user is implemented, and the correlation between the query result and the user query is improved.

A system and method to facilitate expansion, disambiguation, and optimization of search queries over a network wherein an original query received from a user is parsed to obtain at least one query term. A plurality of keywords related contextually to one or more query terms are further retrieved from a database. Finally, a set of modified queries is generated, each modified query further comprising at least one query term and at least one retrieved keyword.

The invention belongs to the field of data mining, aims to solve the problem of excavating core authors in an academic field and intelligently extracting related information of the authors, and provides an improved academic core author excavation and information extraction method and system based on a core node discovery algorithm in the social network analysis technology. The method combines the vertical search technology, the social network analysis technology and the text analysis technology, and can find the core authors or groups of the academic field in the mass of information to further obtain related information of the authors. The method uses the vertical search technology to collect open source literature data, uses the bibliometric technology and the complex network analysis technology to analyze the importance of a variety of social entities in the data, and utilizes a community discovery algorithm to perform entity clustering based on the closeness degree of relationships between entities to find out an academic community. Users can find the core authors or an institution according to an entity importance ranking, and find the leadership team according to published articles amount distribution of cooperative groups.

The invention provides a sending system of information which is needed by a user based on the position of a base station, and the sending system comprises an index information content server, a user subscription server, a user information push server and an information retrieval and read client. The invention also provides a vertical search engine establishment method which utilizes the position of the base station as an index item and faces a mobile terminal to search and an information active push method which is based on the position of the base station. When in use of the sending system, the user only needs to set categories and/or keywords which are interested by the user in advance, when the user moves to certain place, the user can rapidly obtain the information which is near to the current place and is related to the categories which are set by the user; and the user can conveniently obtain the information, thereby the search time is greatly reduced, and the convenience for obtaining the information is improved.

The invention provides an intelligent vertical search method and an intelligent vertical search system, and relates to the technical field of networks. The method comprises the following step of: according to matching results of query words of a user and items which have been classified in the industry in a classified database, acquiring items related with the query words in various classes, displaying the items of the various classes and related information according to classes, wherein the items which have been classified in the industry are acquired by the following steps of: acquiring all items of all webpages of the industry and related information; performing weighted analysis on morphological matching results of key words of various items and key words corresponding to various classes of the industry to determine the classes to which the various items belong; and/or determining the classes to which the various items belong according to the similarity of the appearance frequency rate of various key words of unclassified items and the appearance probability of various key words of the classified items, which is acquired through statistics in advance. By the invention, information related to focuses of users can be displayed more accurately, comprehensively and quickly.

The invention discloses a method for implementing a topical crawler system based on learning URL string information. First, a traditional correlation judgment method of the topical crawler is improved, and a method for judging the correlation between a target URL and a topic based on URL string information, web content, and anchor information is proposed. Information brought by the URL string is learned continuously by adopting a method of machine learning to update relevant vectors of the topic dynamically, and the judgment accuracy of correlation between the target URL and the topic is improved. Finally, a crawler strategy which combines content analysis and link analysis is adopted while computational complexity is not increased, which prevents the topical crawler from trapping in local optimum, improves overallness of the crawler when crawling, and improves efficiency of the crawler. The method of the invention can be used in a crawler module of a vertical search engine to crawl web pages of a particular field.

The invention discloses a webpage classification identifying system based on vertical search and focused crawler technology. The system is characterized by comprising an application expressing module, a data acquisition module and a content analyzing module, wherein the data acquisition module finishes acquisition of webpage data through a Web protocol, and transfers the acquired page data to the content analyzing module; the content analyzing module performs HTML (hyper text mark-up language) analysis on the page data acquired by the data acquisition module, extracts hyperlink in a page and adds the hyperlink into a URL (uniform resource locator) queue to obtain a correspondence table between the website type and URL; and the application expressing module receives the keyword input by a user for search, and feeds the searched website of a specific field and/or the website type thereof back to the user. Through actual operation and test in the development and construction process, the implementation effect of the webpage classification identification method based on vertical search and focused crawler is perfectly reflected, and the accuracy of the method is verified.

The present invention relates to a distributed enterprise information vertical search method. The distributed enterprise information vertical search method comprises: crawling related webpages on websites of related information by using network crawlers through a data acquisition module; cleaning the related crawled webpage data by a data indexing module and establishing an index; receiving query keywords through a comprehensive search module and an enterprise search module, submitting the query keywords to a solr service and inquiring the query keywords from the established index documents; and accomplishing authority management of a system user by virtue of a user authority management module and pushing inquiry results as required according to authority. The distributed enterprise information vertical search method is a professional search method for enterprises and is subdivision and extension of a universal search engine, solves the problems that the universal search engine is great in amount of information, inaccurate to inquire, not enough in depth and the like, and can provide information with a special value and related services in the field of taxation.

The invention discloses a design technology for an object-level personalized vertical search engine. The basic idea of an algorithm is that: related web pages on the Internet are acquired by an adaptive vertical crawler technology, data is subjected to a series of objectification processing such as semantic analysis, extraction, integration and the like, objectified information on the Internet is acquired, and a personalized object ordering result is returned to each user in a search engine mode. The original page data is highly purified and organized by the search engine designed by the technology through a data mining technology, so that the quality of the data is ensured, and the inclusion of illegal information is controlled to the greatest extent. In addition, by a personalized search recommendation technology, the consumption preference of each user can be accurately determined, and the query intention of each user is understood. The object-level personalized vertical semantic search engine is subjected to integrated innovation on the basis of fully learning and absorbing the advantages of semantic search, object-level search and personalized search technologies, and completely accords with the development direction of a next-generation search engine.

A method of IntraBC (Intra-block copy) coding for a coding region is disclosed. Embodiments of the present invention derive an IntraBC (Intra picture block copy) predictor from a constrained previous reconstructed region so as to reduce storage requirement for the previous reconstructed data. In one embodiment, a maximum absolute vertical BV (block vector) value, MaxV_BV is determined, where MaxV_BV is smaller than a full vertical search range for the coding region. A constrained previous reconstructed region corresponding to previous reconstructed samples processed before the current block is then determined, where the constrained previous reconstructed region includes at least MaxV_MV reconstructed samples in vertical direction above the current block and excludes at least one row of reconstructed samples for the current block with a vertical distance larger than MaxV_MV. Each coding block may correspond to a prediction unit (PU) or a coding unit (CU).

The invention discloses a method for searching movie and television contents of the Internet, which comprises the following steps of: A, analyzing webpages of movie and television content websites of the Internet by using a webpage acquisition module through vertical search technology and establishing a content information and management database according to the video and television content information acquired by the webpage acquisition module from the Internet; B, establishing an index information and management database used for storing multiple kinds of content index information according to the content information and management database; and C, acquiring content information required by a user from the index information and management database and the content information and management database by using a search engine according to a content search request input by the user. The method and the system for searching the movie and television contents of the Internet simplify the method and operation for acquiring the movie and television contents from the Internet.

The invention relates to a focusing relevancy ordering method for a vertical search engine. Aiming at the problem that a focused crawler cannot pass through a dark tunnel, the invention improves a focused crawling strategy of the focused crawler by using an on-line learning method and utilizing an auxiliary function, so as to lead the focused crawler to capture subject data with higher relevancy. A PageRank algorithm and an improved algorithm thereof are studied, the webpage clicking action of a user is modeled, and the transferring way of a PageRank value among links is improved, so as to put forward the improved algorithm. As to the disadvantage that the dimensionality of a feature extraction model of webpage weight is over high, a user-defined method of the webpage weight is put forward, so as to define a factor of the webpage weight and measure the weight of the factor of the webpage weight according to the divisibility criterion, thereby providing an evaluation function of the webpage weight and effectively lowering the dimensionality of a webpage feature space. By utilizing the method in the invention, the user can obtain a high-quality search result set when using a subject resource search engine system.

The invention provides a domain-oriented network information search method. By the domain-oriented network information search method, data information can be unified on the same platform, information of multiple data sources can be searched, and various formats of data including structured, semi-structured and unstructured data are supported. The domain-oriented network information search method which is a network information acquisition method includes steps of enabling domain experts to specify domain website sets, submitting keywords according to domain characteristics and creating a domain keyword bank; compiling information acquisition strategies according to link and content analysis and then acquiring target web pages in domain websites; and extracting, filtering and classifying acquired information of the web pages, creating a database and storing the information according to an inverted index. The domain-oriented network information search method is specifically implemented by a web page acquisition spider module, a classifier training module and a data index module. The domain-oriented network information search method is high in adaptability and topic relevance, and a vertical search engine using the method as a core is high in recall ratio and precision ratio.