Difference between revisions of "Document representation and query expansion models for blog recommendation"
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| − | + | We explore several different document representation models and two query expansion models for the task of recommending blogs to a user in response to a query. Blog relevance ranking differs from traditional document ranking in ad-hoc information retrieval in several ways: (1) the unit of output (the blog) is composed of a collection of documents (the blog posts) rather than a single document, (2) the query represents an ongoing – and typically multifaceted – interest in the topic rather than a passing ad-hoc information need and (3) due to the propensity of spam, splogs, and tangential comments, the blogosphere is particularly challenging to use as a source for high-quality query expansion terms. We address these differences at the document representation level, by comparing retrieval models that view either the blog or its constituent posts as the atomic units of retrieval, and at the query expansion level, by making novel use of the links and anchor text in Wikipedia1 to expand a user’s initial query. We develop two complementary models of blog retrieval that perform at comparable levels of precision and recall. We also show consistent and significant improvement across all models using our Wikipedia expansion strategy. | |
== Summary == | == Summary == | ||
Revision as of 00:33, 5 November 2012
This is a summary of research paper as part of Social Media Analysis 10-802, Fall 2012.
Contents
Citation
J. Arguello, J. L. Elsas, J. Callan, and J. G. Carbonell. Document representation and query expansion models for blog recommendation. In Proc. of the 2nd Intl. Conf. on Weblogs and Social Media (ICWSM), 2008.
Online Version
Abstract from the paper
We explore several different document representation models and two query expansion models for the task of recommending blogs to a user in response to a query. Blog relevance ranking differs from traditional document ranking in ad-hoc information retrieval in several ways: (1) the unit of output (the blog) is composed of a collection of documents (the blog posts) rather than a single document, (2) the query represents an ongoing – and typically multifaceted – interest in the topic rather than a passing ad-hoc information need and (3) due to the propensity of spam, splogs, and tangential comments, the blogosphere is particularly challenging to use as a source for high-quality query expansion terms. We address these differences at the document representation level, by comparing retrieval models that view either the blog or its constituent posts as the atomic units of retrieval, and at the query expansion level, by making novel use of the links and anchor text in Wikipedia1 to expand a user’s initial query. We develop two complementary models of blog retrieval that perform at comparable levels of precision and recall. We also show consistent and significant improvement across all models using our Wikipedia expansion strategy.
Summary
Overview
This paper proposes some techniques for query expansion for document representation which is used for blog recommendation.
Proposed Techniques
Evaluation
Discussion
Related Papers
Study Plan
Resources useful for understanding this paper
