In search of knowledge-based search tactics

Smith, Philip J.; Shute, Steven J.; Galdes, D.

doi:10.1145/75335.75336

Cited by 2 publications

(2 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Although early work in IR (Croft and Lewis, 1987;Smith et al, 1989) along these lines have not been successful, recent attempts in question answering (Harabagiu et al, 2000;Small et al, 2004;Demner-Fushman and Lin, 2007) have demonstrated the effectiveness of frame-based retrieval. Recent work on structured queries (Bilotti et al, 2007) lends additional support to the effectiveness of automatic facet analysis, since there is often a correspondence between query clauses and facets.…”

Section: Mediated Search As a Retrieval Modelmentioning

confidence: 99%

Toward automatic facet analysis and need negotiation

Lin

Abels

2008

ACM Trans. Inf. Syst.

View full text Add to dashboard Cite

This work explores the hypothesis that interactions between a trained human search intermediary and an information seeker can inform the design of interactive IR systems. We discuss results from a controlled Wizard-of-Oz case study, set in the context of the TREC 2005 HARD track evaluation, in which a trained intermediary executed an integrated search and interaction strategy based on conceptual facet analysis and informed by need negotiation techniques common in reference interviews. Having a human "in the loop" yielded large improvements over fully-automated systems as measured by standard ranked-retrieval metrics, demonstrating the value of mediated search. We present a detailed analysis of the intermediary's actions to gain a deeper understanding of what worked and why. One contribution is a taxonomy of clarification types informed both by empirical results and existing theories in library and information science. We discuss how these findings can guide the development of future systems. Overall, this work illustrates how studying humaninformation seeking processes can lead to better information retrieval applications.

show abstract

Section: Mediated Search As a Retrieval Modelmentioning

confidence: 99%

Toward automatic facet analysis and need negotiation

Lin

Abels

2008

ACM Trans. Inf. Syst.

View full text Add to dashboard Cite

show abstract

“…In order to evaluate the contents that are associated with the semantics of the data being retrieved, a database management system requires knowledge for interpreting raw data into the contents implied. Knowledgeassisted retrieval is also studied in the area of textual databases [40], [52]. However, it plays a more important role for multimedia database retrieval because even a single media data has many faces of meaning/contents, one of which should actually be referred to in query evaluation depending on a context of retrieval.…”

Section: Introductionmentioning

confidence: 99%

A survey on content-based retrieval for multimedia databases

Adachi

Ichikawa

1999

IEEE Trans. Knowl. Data Eng.

277

123

View full text Add to dashboard Cite

Abstract-Conventional database systems are designed for managing textual and numerical data, and retrieving such data is often based on simple comparisons of text/numerical values. However, this simple method of retrieval is no longer adequate for the multimedia data, since the digitized representation of images, video, or data itself does not convey the reality of these media items. In addition, composite data consisting of heterogeneous types of data also associates with the semantic content acquired by a user's recognition. Therefore, content-based retrieval for multimedia data is realized taking such intrinsic features of multimedia data into account. Implementation of the content-based retrieval facility is not based on a single fundamental, but is closely related to an underlying data model, a priori knowledge of the area of interest, and the scheme for representing queries. This paper surveys recent studies on content-based retrieval for multimedia databases from the point of view of three fundamental issues. Throughout the discussion, we assume databases that manage only nontextual/numerical data, such as image or video, are also in the category of multimedia databases.

show abstract

In search of knowledge-based search tactics

Cited by 2 publications

References 7 publications

Toward automatic facet analysis and need negotiation

Toward automatic facet analysis and need negotiation

A survey on content-based retrieval for multimedia databases

Contact Info

Product

Resources

About