Techniques for Specialized Search Engines

Abstract: In this paper, we present Web search engine, a prototype of a Web search engine that makes heavy use of the structure present in hypertext. Google is designed to crawl, index the Web efficiently, and produce much more satisfying search results than existing systems. The prototype with a full text and hyperlink database of at least 24 million pages is available at http://google.stanford.edu/ to engineer a search engine is a challenging task. Search engines index tens to hundreds of millions of web pages involving a comparable number of distinct terms. They answer tens of millions of queries every day. Despite the importance of large-scale search engines on the web, very little academic research has been done on them. Furthermore, due to rapid advance in technology and web proliferation, creating a web search engine today is very different from three years ago. This paper provides an in-depth description of our large-scale web search engine -- the first such detailed public description we know of to date. Apart from the problems of scaling traditional search techniques to data of this magnitude, there are new technical challenges involved with using the additional information present in hypertext to produce better search results. This paper addresses this question of how to build a practical large-scale system that can exploit the additional information present in hypertext. In addition, we look at the problem of how to effectively deal with uncontrolled hypertext collections where anyone can publish anything they want. Keywords: World Wide Web, Search Engines, Information Retrieval, PageRank, Google. Title: WEB SEARCH ENGINE Author: Raghav Arora, Rana Rahul Sathyaprakash, Saurabh Rauthan, Shrey Jakhetia International Journal of Computer Science and Information Technology Research ISSN 2348-120X (online), ISSN 2348-1196 (print) Research Publish Journals

The World Wide Web ("WWW", or simply "Web") is an information space that allows us to share information from global data repositories. To find out user specific data the web uses specialized tools known as web search engines. These search engines are a remotely accessible program that does keyword searches for information on the Internet. As there is tremendous growth in the volume of data or the information it is difficult to get syntactically relevant documents with in less time using conventional search engines. It can be possible with semantic web by providing sufficient context about resources on the web and building the semantic search engines that use the context so that machines can find out the meaningful documents. In this paper we present study on the general search engines and semantic search engines and have done a survey on how the keyword based search engine work for a user query practically and how semantic search engines provides results differently depending upon their specific performance

Proceedings of the ASIST Annual Meeting, 1996

Three Web search engines, namely, Alta Vista, Excite, and Lycos, were compared and evaluated in terms of their search capabilities (e.g., Boolean logic, truncation, field search, word and phrase search) and retrieval performances (i.e., precision and response time) using sample queries drawn from real reference questions. Recall, the other evaluation criterion of information retrieval, is deliberately omitted from this study because it is impossible to assume how many relevant items there are for a particular query in the huge and ever changing Web system. The authors of this study found that Alta Vista outperformed Excite and Lycos in both search facilities and retrieval performance although Lycos had the largest coverage of Web resources among the three Web search engines examined. As a result of this research, we also proposed a methodology for evaluating other Web search engines not included in the current study. 6. Out of the 10 downloaded Web records, there are 2 duplicates. 7. All the figures were obtained in January 1996.

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Many information resources available over the Internet only provide browsing and pre-defined navigation capabilities. If the user is interested in simple word matches on documents as a whole, search engines such as Yahoo or AltaVista may be adequate. For resources of high volume, the user should be able to specify preferences and just obtain the relevant portions of a resource. In this paper, we study the problem of enhancing the search capability to an existing resource by implementing and evaluating two approaches: use of (i) structured (relational) database or, (ii) HTML documents enhanced with meta tags.