Difference between revisions of "Document representation and query expansion models for blog recommendation"
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== Abstract from the paper == | == 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 | + | 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 Wikipedia 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 == | ||
=== Overview === | === Overview === | ||
| − | This [[Category::Paper|paper]] | + | This [[Category::Paper|paper]] explores different [[AddressesProblem::Document representation|document representation]] models and [[AddressesProblem::Query expansion|query expansion]] techniques for blog recommendation task as compared to traditional ad-hoc information retrieval task. They are mainly attempting to provide a suitable ranked list of blogs which can satisfy the user's information need represented solely through his/her query. Some of the differences between blog retrieval and ad-hoc retrieval as pointed out by the authors are |
| + | * Relevance of blog to a query depends on all the posts in it rather than a single document as in ad-hoc retrieval | ||
| + | * Relevance of just on post may not make the entire blog good for recommendation | ||
| + | * A short query may not represent accurately the user's information need and his/her interests on various aspects of discussions usually present on blogs | ||
| + | * Blogs contain lot of noise in the form of reader comments, spams unlike traditional documents | ||
| − | === | + | In order to address these differences from ad-hoc retrieval, the authors explore two aspects in blog retrieval - Blog(Document) representation and Query expansion. |
| + | |||
| + | === Blog Representation === | ||
| + | They propose two different blog representation models - Large document and Small document models. | ||
| + | |||
| + | ==== Large Document Representation Model ==== | ||
| + | |||
| + | ==== Small Document Representation Model ==== | ||
| + | |||
| + | |||
| + | === Query Expansion === | ||
== Evaluation == | == Evaluation == | ||
| Line 25: | Line 39: | ||
== Study Plan == | == Study Plan == | ||
Resources useful for understanding this paper | Resources useful for understanding this paper | ||
| + | * Article - Information Retrieval | ||
| + | * Blog recommendation - TREC 2007 Task | ||
| + | * Document representation models in IR | ||
| + | * Query expansion models in IR | ||
Revision as of 17:54, 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 Wikipedia 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 explores different document representation models and query expansion techniques for blog recommendation task as compared to traditional ad-hoc information retrieval task. They are mainly attempting to provide a suitable ranked list of blogs which can satisfy the user's information need represented solely through his/her query. Some of the differences between blog retrieval and ad-hoc retrieval as pointed out by the authors are
- Relevance of blog to a query depends on all the posts in it rather than a single document as in ad-hoc retrieval
- Relevance of just on post may not make the entire blog good for recommendation
- A short query may not represent accurately the user's information need and his/her interests on various aspects of discussions usually present on blogs
- Blogs contain lot of noise in the form of reader comments, spams unlike traditional documents
In order to address these differences from ad-hoc retrieval, the authors explore two aspects in blog retrieval - Blog(Document) representation and Query expansion.
Blog Representation
They propose two different blog representation models - Large document and Small document models.
Large Document Representation Model
Small Document Representation Model
Query Expansion
Evaluation
Discussion
Related Papers
Study Plan
Resources useful for understanding this paper
- Article - Information Retrieval
- Blog recommendation - TREC 2007 Task
- Document representation models in IR
- Query expansion models in IR
