Facet Mining from Annotated Web Pages

Facet Mining from Annotated Web Pages
Author(s):
SIJIN P, CHAMPA H N
Keywords:
Item ranking, Facet, Data Point, Facet quality.
Abstract
The query dependent multidimensional views of a search query which describe and summarize some important aspects of search are called facets. The Faceted search allows the users to search on a facet list of a query to pick out the desired one without browsing for a long time. The proposed facet mining framework called Facet Mining from Annotated Documents (FMAD) integrates keyword search by category browsing and produces an interface which has several conceptual dimensions. The FMAD is designed to achieve an interactive data summarization process by liberalizing topic identification and interpretation on user side called faceted search. The proposed ontology based query dependent facet framework follows a series of phases from initial facet weighting to facet item ranking in order to produce high quality clusters. The proposed Quality Threshold with Weighted Data Point and Web Page Count (WQTWC) algorithm is used to produce group of items which are similar in same group clusters and differ with other group clusters. In FMAD facets are automatically extracted from document description, annotated documents, and metadata records.
Article Details
Unique Paper ID: 153423 Publication Volume & Issue: Volume 8, Issue 7 Page(s): 146 - 153
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