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Kansas State University

Capturing semantics using a link analysis based concept extractor approach

Abstract

dc:description.abstract

The web contains a massive amount of information and is continuously growing every day. Extracting information that is relevant to a user is an uphill task. Search engines such as Google TM, Yahoo! TM have made the task a lot easier and have indeed made people much more "smarter". However, most of the existing search engines still rely on the traditional keyword-based searching techniques i.e. returning documents that contain the keywords in the query. They do not take the associated semantics into consideration. To incorporate semantics into search, one could proceed in at least two ways. Firstly, we could plunge into the world of "Semantic Web", where the information is represented in formal formats such as RDF, N3 etc which can effectively capture the associated semantics in the documents. Secondly, we could try to explore a new semantic world in the existing structure of World Wide Web (WWW). While the first approach can be very effective when semantic information is available in RDF/N3 formats, for many web pages such information is not readily available. This is why we consider the second approach in this work. In this work, we attempt to capture the semantics associated with a query by rst extracting the concepts relevant to the query. For this purpose, we propose a novel Link Analysis based Concept Extractor (LACE) that extract the concepts associated with the query by exploiting the meta data of a web page. Next, we propose a method to determine relationships between a query and its extracted concepts. Finally, we show how LACE can be used to compute a statistical measure of semantic similarity between concepts. At each step, we evaluate our approach by comparison with other existing techniques (on benchmark data sets, when available) and show that our results are competitive with existing state of the art results or even outperform them.

Degree

thesis:*
Grantor dc:publisher
Kansas State University
Year dc:date.issued
2009

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Kulkarni, Swarnim

Subjects

dc:subject × 4

Rights

dc:rights
Statement dc:rights
  • © the author. This Item is protected by copyright and/or related rights. You are free to use this Item in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you need to obtain permission from the rights-holder(s).
Language dc:language.iso
en_US

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/2097/1526
OAI identifier oai:identifier
oai:krex.k-state.edu:2097/1526

Chain of custody

source
Harvested from
Kansas State University
Base URL
krex.k-state.edu/server/oai/request
Last updated
2026-07-27
Source record
OAI-PMH GetRecord
citation

Kulkarni, Swarnim. Capturing semantics using a link analysis based concept extractor approach. Kansas State University, 2009. http://hdl.handle.net/2097/1526