Based on search engine , this paper built a Web information retrieval matching and structure extraction model. And realized the algorithm of locating and automatically extracting multi-web Baidu news information. Getting the standard mathematical expression of URLs by analyzing the search results URLs and analyzing the DOM tree structure of web pages, this article designed the key tags regular ...

This paper describes one of the ways how to overcome some of the major limitations of current fulltext search engines. It deals with synonymy of the web search engine results by clustering them into relevant synonym category of given word. It employs WordNet lexical database and several linguistic approaches to classify results in search engine result page (SERP) in appropriate synonym category...

Everyone knows that to search any information from Internet we need Search Engine. But user doesn’t typically like to search one topic for a long time. To offer a better solution, we introduce a Web-search Engine which is based on an Ontology to retrieve relevant pages. To make the search faster, we incorporate a new concept called Index based on High Efficient Relevant page Tree. This tree con...

Traditional search engines create their indices by spidering or crawling surface Web pages. To be discovered, the page must be static and linked to other pages. Traditional search engines can not "see" or retrieve content in the deep Web -those pages do not exist until they are created dynamically as the result of a specific search. Because traditional search engine crawlers can not probe benea...

Modern search engine result pages often contain a mixture of results from structured and unstructured sources. Where such mixtures of structured and unstructured information are called for, the state-of-the-art is to organize complex search engine result pages around entities. Generating such a mixture of entity-oriented results in response to a traditional keyword query raises a number of inte...

User click behaviors reflect his preference in Web search processing objectively, and it is very important to give a proper interpretation of user click for improving search results. Previous click models explore the relationship between user examines and latent clicks web document obtained by search result page via multiple-click model, such as the independent click model(ICM) or the dependent...

Searching online has become part of the everyday lives of most people. Whether to look for information about the latest gadget to getting directions to a popular trend, most people have made search engines part of their daily routine. Beyond trivial applications, search engines are increasingly becoming the sole or primary source directing people to essential information. For this reason, searc...

Traditional World Wide Web search engines, such as AltaVista.com, index and recommend individual Web pages to assist users in locating relevant documents. As the Web grows, however, the number of matching pages increases at a tremendous rate. Users are often overwhelmed by the large answer set recommended by the search engines. Also, if a matching document is a hypertext, the document structure...

Web search engines help users find relevant web pages by returning a result set containing the pages that best match the user’s query. When the identified pages have low relevance, the query must be refined to capture the search goal more effectively. However, finding appropriate refinement terms is difficult and time consuming for users, so researchers developed query expansion approaches to i...