Performance standards and evaluations in IR test collections: Cluster-based retrieval models

Shaw, W. M.; Burgin, Robert; Howell, Patrick

doi:10.1016/s0306-4573(96)00043-x

Cited by 87 publications

(41 citation statements)

References 35 publications

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“…Most clustering research in IR is related to cluster search effectiveness [Griffiths et al, 1986;Willett, 1988;Burgin 1995;Shaw et al 1997;Schütze, Craig 1997]. The research on efficiency aspects of cluster searches is limited.…”

Section: Previous and Related Workmentioning

confidence: 99%

Efficiency and effectiveness of query processing in cluster-based retrieval

Can

Altıngövde

Demir

2004

Information Systems

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Our research shows that for large databases, without considerable additional storage overhead, clusterbased retrieval (CBR) can compete with the time efficiency and effectiveness of the inverted indexbased full search (FS). The proposed CBR method employs a storage structure that blends the cluster membership information into the inverted file posting lists. This approach significantly reduces the cost of similarity calculations for document ranking during query processing and improves efficiency. For example, in terms of in-memory computations, our new approach can reduce query processing time to 39% of FS. The experiments confirm that the approach is scalable and system performance improves with increasing database size. In the experiments, we use the Cover Coefficient-based Clustering Methodology (C 3 M), and the Financial Times database of TREC-4 containing 210,158 documents of size 564 MB defined by 229,748 terms with total of 29,545,234 inverted index elements. This study provides CBR efficiency and effectiveness experiments using the largest corpus in an environment that employs no user interaction or user behavior assumption for clustering.

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Section: Previous and Related Workmentioning

confidence: 99%

Efficiency and effectiveness of query processing in cluster-based retrieval

Can

Altıngövde

Demir

2004

Information Systems

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“…As evaluation metric, we used the F 1 score, 39 i.e., the harmonic mean of precision and recall, using the following formula:…”

Section: Resultsmentioning

confidence: 99%

Reference Information Extraction and Processing Using Random Conditional Fields

Groza

Grimnes

Handschuh

2012

ITAL

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“…The MED1033 database, composed of 1033 documents extracted from the National Library of Medicine's database, was used for other analyses. Because of the design of this database, it is easier for systems using MED1033 to retrieve documents labeled as relevant (Kwok, 1990;Shaw, Burgin, & Howell, 1997). The MED1033 Tagged database is part-of-speech tagged as with the CF POS Tagged database.…”

Section: Resultsmentioning

confidence: 99%

Percent perfect performance (PPP)

Losee

2007

Information Processing & Management

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An information retrieval performance measure that is interpreted as the percent of perfect performance (PPP) can be used to study the effects of the inclusion of specific document features or feature classes or techniques in an information retrieval system. Using this, one can measure the relative quality of a new ranking algorithm, the result of incorporating specific types of metadata or folksonomies from natural language, or determine what happens when one makes modifications to terms, such as stemming or adding part-of-speech tags. For example, knowledge that removing stopwords in a specific system improves the performance ¡ £ ¢ of the way from the level of random performance to the best possible result is relatively easy to interpret and to use in decision making; using this percent based measure also allows us to simply compute and interpret that there remains ¤ ¡ £ ¢ of the possible performance to be obtained using other methods. The PPP measure as used here is based on the Average Search Length, a measure of the ordering quality of a set of data, and may be used when evaluating all the documents or just the first ¥ documents in an ordered list of documents. Because the ASL may be computed empirically or may be estimated analytically, the PPP measure may also be computed empirically or performance may be estimated analytically. Different levels of upper bound performance are discussed.

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Performance standards and evaluations in IR test collections: Cluster-based retrieval models

Cited by 87 publications

References 35 publications

Efficiency and effectiveness of query processing in cluster-based retrieval

Efficiency and effectiveness of query processing in cluster-based retrieval

Reference Information Extraction and Processing Using Random Conditional Fields

Percent perfect performance (PPP)

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