Engineering a multi-purpose test collection for Web retrieval experiments

Bailey, Peter; Craswell, Nick; Hawking, David

doi:10.1016/s0306-4573(02)00084-5

Cited by 119 publications

(86 citation statements)

References 10 publications

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“…9. The probability that the degree of a vertex exceeds x in (a) the largest five networks of Table I and (b) the smallest five networks in Table I. 042309-12 [12], (b) Baidu encyclopedia [12], (c) WordNet [13], (d) TREC-WT10g web graph [14], (e) Google web graph [11], (f) Internet on the autonomous systems level [11], (g) Catster and Dogster social networks [15], (h) Gowalla social network [11], and (i) Wikipedia communication network [11]. The different shadings indicate the theoretical boundaries of the regimes as in Fig.…”

Section: Appendix C: From Hidden Variables To Degreesmentioning

confidence: 99%

Clustering spectrum of scale-free networks

et al. 2017

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Real-world networks often have power-law degrees and scale-free properties, such as ultrasmall distances and ultrafast information spreading. In this paper, we study a third universal property: three-point correlations that suppress the creation of triangles and signal the presence of hierarchy. We quantify this property in terms ofc(k), the probability that two neighbors of a degree-k node are neighbors themselves. We investigate how the clustering spectrum k →c(k) scales with k in the hidden-variable model and show thatc(k) follows a universal curve that consists of three k ranges wherec(k) remains flat, starts declining, and eventually settles on a power-lawc(k) ∼ k −α with α depending on the power law of the degree distribution. We test these results against ten contemporary real-world networks and explain analytically why the universal curve properties only reveal themselves in large networks.

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Section: Appendix C: From Hidden Variables To Degreesmentioning

confidence: 99%

Clustering spectrum of scale-free networks

et al. 2017

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“…The collection to be searched for this task is the WT10g collection [2], a 10 gigabytes subset of the VLC2 collection which in turn is a subset of a 1997 crawl of the WWW done by the Internet Archive 5 . WT10g is designed to have a relatively high density of inter-server hyperlinks.…”

Section: Worldnet Africa Hunt Memorial Library Haas Business School Umentioning

confidence: 99%

The Importance of Prior Probabilities for Entry Page Search

Kraaij¹,

Westerveld

Hiemstra

2002

Proceedings of the 25th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval

175

136

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An important class of searches on the world-wide-web has the goal to find an entry page (homepage) of an organisation. Entry page search is quite different from Ad Hoc search. Indeed a plain Ad Hoc system performs disappointingly. We explored three non-content features of web pages: page length, number of incoming links and URL form. Especially the URL form proved to be a good predictor. Using URL form priors we found over 70% of all entry pages at rank 1, and up to 89% in the top 10. Non-content features can easily be embedded in a language model framework as a prior probability.

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“…Tables III, IV, V and Tables VI, VII, VIII, respectively, we can see the effect of using the two different test collections. Both collections were designed to possess the basic properties of the Web (Bailey et al, 2003). However, it has been noted in TREC10 (Hawking and Craswell, 2001) and TREC11 (Craswell and Hawking, 2002) that using link analysis for the TREC10 topic relevance task and the TREC11 topic distillation task, hardly improves the retrieval effectiveness.…”

Section: Analysis Of Resultsmentioning

confidence: 99%

Dempster-Shafer Theory for a Query-Biased Combination of Evidence on the Web

Plachouras

Ounis

2005

Inf Retrieval

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Abstract. This paper reports on a large-scale experiment for the evaluation of a formal query-biased combination of evidence mechanism. We use the DempsterShafer theory of evidence to combine optimally results obtained by content and link analyses on the Web. The query-biased mechanism is based on the query scope, a measure of the query specificity. The query scope is defined using a probabilistic propagation mechanism on top of the hierarchical structure of concepts provided by WordNet. We use two standard Web test collections and two different link analysis approaches. The results show that the proposed approach could improve the retrieval effectiveness.

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Engineering a multi-purpose test collection for Web retrieval experiments

Cited by 119 publications

References 10 publications

Clustering spectrum of scale-free networks

Clustering spectrum of scale-free networks

The Importance of Prior Probabilities for Entry Page Search

Dempster-Shafer Theory for a Query-Biased Combination of Evidence on the Web

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