@inproceedings{cdf3c428cd624c25b5651a33cd14defa,
title = "Concept level web search via semantic clustering",
abstract = "Internet search engine techniques have evolved from simple web searching using categorization (e.g., Yahoo) to advanced page ranking algorithms (e.g., Google). However, the challenge for the next generation of search algorithms is not the quantity of search results, but identifying the most relevant pages based on a semantic understanding of user requirements. This notion of relevance is closely tied to the semantics associated with the term being searched. The ideal situation would be to represent results in an intuitive way that allows the user to view their search results in terms of concepts related to their search word or phrase rather than a list of ranked web pages. In this paper, we propose a semantic clustering approach that can be used to build a conceptual search engine.",
keywords = "Conceptual search, Document clustering, Information retrieval, Search engine",
author = "Nian Yan and Deepak Khazanchi",
year = "2007",
doi = "10.1007/978-3-540-72588-6_130",
language = "English (US)",
isbn = "9783540725879",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
number = "PART 3",
pages = "806--812",
booktitle = "Computational Science - ICCS 2007 - 7th International Conference, Proceedings",
edition = "PART 3",
note = "7th International Conference on Computational Science, ICCS 2007 ; Conference date: 27-05-2007 Through 30-05-2007",
}