Temporal profiles of queries

Jones, Rosie; Dı́az, Fernando

doi:10.1145/1247715.1247720

Cited by 172 publications

(195 citation statements)

References 13 publications

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“…older or newer). This behavior is different from the observed in other search services, such as in news search, where recent and updated information is preferred [19]; (2) highly relevant documents for a topic may exist throughout the entire search period, despite being known that some periods tend to concentrate more relevant documents [20]. -topical relevance for a given navigational topic.…”

Section: Relevance Propagationmentioning

confidence: 68%

Evaluating Web Archive Search Systems

Costa

Silva

2012

Web Information Systems Engineering - WISE 2012

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Abstract. The information published on the web, a representation of our collective memory, is rapidly vanishing. At least 77 web archives have been developed to cope with the web's transience problem, but despite their technology having achieved a good maturity level, the retrieval effectiveness of the search services they provide still presents unsatisfactory results. In this work, we propose an evaluation methodology for web archive search systems based on a list of requirements compiled from previous characterizations of web archives and their users. The methodology includes the design of a test collection and the selection of evaluation measures to support realistic and reproducible experiments. The test collection enabled, for the first time, to measure the effectiveness of state-of-the-art IR technology employed in web archives. Results confirm the poor quality of search results retrieved with such technology. However, we show how to combine temporal features, along with the regular topical features, to improve the search effectiveness on web archives. The test collection is available to the research community.

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Section: Relevance Propagationmentioning

confidence: 68%

Evaluating Web Archive Search Systems

Costa

Silva

2012

Web Information Systems Engineering - WISE 2012

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“…This important subfield of IR has the goal to improve search effectiveness by exploiting temporal information in documents and queries [11,12]. The temporal dimension leads to new challenges in query understanding [13], retrieval models [14,15] as well as temporal indexing [16,17]. However, most temporal indexing approaches treat documents as static texts with a certain validity, which does not account for the dynamics in Web archives as described above.…”

Section: Web Archive Searchmentioning

confidence: 99%

Accessing web archives from different perspectives with potential synergies

Holzmann¹,

Risse²

2017

Researchers, Practitioners and Their Use of the Archived Web

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Abstract. Web archives constitute a valuable source for researchers from many disciplines. However, their sheer size, the typically broad scope and their temporal dimension make them difficult to work with. We have identified three approaches to access and explore Web archives from different perspectives: user-, data-and graph-centric. In this paper we present related works on these three views as well as discuss their relations and potential synergies. Finally, we propose a generic analysis schema that outlines a systematic way to study Web archives by approaching them from different zoom levels corresponding to the three presented views.

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“…We refer to work from query log analysis such as (Pass et al, 2006;Jansen et al, 2000;Jones & Diaz, 2007) which analyze different aspects of queries, e.g., temporal aspects. While evaluation strategies appear to be similar, the intention behind query log analysis often is to improve retrieval performance.…”

Section: And Support Vectormentioning

confidence: 99%

Acquiring knowledge about human goals from Search Query Logs

Strohmaier

Kroll

2012

Information Processing & Management

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A better understanding of what motivates humans to perform certain actions is relevant for a range of research challenges including generating action sequences that implement goals (planning). A first step in this direction is the task of acquiring knowledge about human goals. In this work, we investigate whether Search Query Logs are a viable source for extracting expressions of human goals. For this purpose, we devise an algorithm that automatically identifies queries containing explicit goals such as find home to rent in Florida. Evaluation results of our algorithm achieve useful precision/recall values. We apply the classification algorithm to two large Search Query Logs, recorded by AOL and Microsoft Research in 2006, and obtain a set of ∼110.000 queries containing explicit goals. To study the nature of human goals in Search Query Logs, we conduct qualitative, quantitative and comparative analyses. Our findings suggest that Search Query Logs (i) represent a viable source for extracting human goals, (ii) contain a great variety of human goals and (iii) contain human goals that can be employed to complement existing commonsense knowledge bases. Finally, we illustrate the potential of goal knowledge for addressing following application scenario: to refine and extend commonsense knowledge with human goals from Search Query Logs. This work is relevant for (i) knowledge engineers interested in acquiring human goals from textual corpora and constructing knowledge bases of human goals (ii) researchers interested in studying characteristics of human goals in Search Query Logs.

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Temporal profiles of queries

Cited by 172 publications

References 13 publications

Evaluating Web Archive Search Systems

Evaluating Web Archive Search Systems

Accessing web archives from different perspectives with potential synergies

Acquiring knowledge about human goals from Search Query Logs

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