Retrieval and feedback models for blog feed search

Elsas, Jonathan L.; Arguello, Jaime; Callan, Jamie; Carbonell, Jaime G.

doi:10.1145/1390334.1390394

Cited by 112 publications

(145 citation statements)

References 8 publications

(9 reference statements)

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“…Elsas et al [2] utilize the link structure of Wikipedia for QE in a Blog distillation task and yield significant improvement for retrieval effectiveness, this work also showed that standard PRF does not perform well in a Blog distillation task. Yang et al [3] classify user queries into three types: entity queries, ambiguous queries, and broader queries.…”

Section: Background and Related Workmentioning

confidence: 84%

External Query Reformulation for Text-Based Image Retrieval

Min

Jones

2011

String Processing and Information Retrieval

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Abstract. In text-based image retrieval, the Incomplete Annotation Problem (IAP) can greatly degrade retrieval effectiveness. A standard method used to address this problem is pseudo relevance feedback (PRF) which updates user queries by adding feedback terms selected automatically from top ranked documents in a prior retrieval run. PRF assumes that the target collection provides enough feedback information to select effective expansion terms. This is often not the case in image retrieval since images often only have short metadata annotations leading to the IAP. Our work proposes the use of an external knowledge resource (Wikipedia) in the process of refining user queries. In our method, Wikipedia documents strongly related to the terms in user query ("definition documents") are first identified by title matching between the query and titles of Wikipedia articles. These definition documents are used as indicators to re-weight the feedback documents from an initial search run on a Wikipedia abstract collection using the Jaccard coefficient. The new weights of the feedback documents are combined with the scores rated by different indicators. Query-expansion terms are then selected based on these new weights for the feedback documents. Our method is evaluated on the ImageCLEF WikipediaMM image retrieval task using text-based retrieval on the document metadata fields. The results show significant improvement compared to standard PRF methods.

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Section: Background and Related Workmentioning

confidence: 84%

External Query Reformulation for Text-Based Image Retrieval

Min

Jones

2011

String Processing and Information Retrieval

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“…For example, MacKinnon and Vechtomova (2008) expanded queries in the Complex interactive Question Answering (CiQA) track of TREC, by first mapping the terms and phrases in a query to Wikipedia article titles, and then expanding them with anchor texts pointing to these articles. Elsas et al (2008) proposed another method of selecting and weighting anchor texts as QE terms, which showed performance gains in the distillation task of the Blog track. While anchor texts may be useful as QE terms in opinion retrieval, we did not explore their use in this paper, focusing instead on the use of page redirects.…”

Section: Expanding Facets With New Conceptsmentioning

confidence: 99%

Facet-based opinion retrieval from blogs

Vechtomova¹

2010

Information Processing & Management

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The paper presents methods of retrieving blog posts containing opinions about an entity expressed in the query. The methods use a lexicon of subjective words and phrases compiled from manually and automatically developed resources. One of the methods uses the Kullback-Leibler divergence to weight subjective words occurring near query terms in documents, another uses proximity between the occurrences of query terms and subjective words in documents, and the third combines both factors. Methods of structuring queries into facets, facet expansion using Wikipedia, and a facet-based retrieval are also investigated in this work. The methods were evaluated using the TREC 2007 and 2008 Blog track topics, and proved to be highly effective.

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“…Within blog (post) search, the TREC Blog track [23,17] plays an important role; having started in 2006, many approaches to blog post finding have been deployed. Among these approaches are the use of credibility indicators [31], recency and link structure [21], and query expansion on external corpora [32,8].…”

Section: Related Workmentioning

confidence: 99%

“…Various ways of improving aspect recall have been introduced: Kurland et al [13] provide an iterative "pseudo-query" generation technique to uncover multiple aspects of a query, using cluster-based language models. Weerkamp and de Rijke [32] explore the use of external corpora to uncover multiple viewpoints on a topic, an approach similar to [8]. Recently, the issue of aspect recall has been addressed using example documents, provided by the user, from which new query terms are sampled [2].…”

Section: Related Workmentioning

confidence: 99%

Using Contextual Information to Improve Search in Email Archives

Weerkamp

Balog

Rijke

2009

Lecture Notes in Computer Science

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Abstract. In this paper we address the task of finding topically relevant email messages in public discussion lists. We make two important observations. First, email messages are not isolated, but are part of a larger online environment. This context, existing on different levels, can be incorporated into the retrieval model. We explore the use of thread, mailing list, and community content levels, by expanding our original query with term from these sources. We find that query models based on contextual information improve retrieval effectiveness. Second, email is a relatively informal genre, and therefore offers scope for incorporating techniques previously shown useful in searching user-generated content. Indeed, our experiments show that using query-independent features (email length, thread size, and text quality), implemented as priors, results in further improvements.

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Retrieval and feedback models for blog feed search

Cited by 112 publications

References 8 publications

External Query Reformulation for Text-Based Image Retrieval

External Query Reformulation for Text-Based Image Retrieval

Facet-based opinion retrieval from blogs

Using Contextual Information to Improve Search in Email Archives

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