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Proceedings - Web 2004

Overview of the TREC 2004 Web Track

Nick Craswell, David Hawking

Abstract

This year's main experiment involved processing a mixed query stream, with an even mix of each query type studied in TREC-2003: 75 homepage finding queries, 75 named page finding queries and 75 topic distillation queries. The goal was to find ranking approaches which work well over the 225 queries, without access to query type labels. We also ran two small experiments. First, participants were invited to submit classification runs, attempting to correctly label the 225 queries by type. Second, we invited participants to download the new W3C test collection, and think about appropriate experiments for the proposed TREC-2005 Enterprise Track. This is the last year for the Web Track in its current form, it will not run in TREC-2005.

Bibtex 
@inproceedings{DBLP:conf/trec/CraswellH04,
    author = {Nick Craswell and David Hawking},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Overview of the {TREC} 2004 Web Track},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/WEB.OVERVIEW.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/CraswellH04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Melbourne University 2004: Terabyte and Web Tracks

Vo Ngoc Anh, Alistair Moffat

Abstract

The University of Melbourne carried out experiments in the Terabyte and Web tracks of TREC 2004. We applied a further variant of our impact-based retrieval approach by integrating evidence from text content, anchor text, URL depth, and link structure into the process of ranking documents, working toward a retrieval system that handles equally well all of the four query types employed in these two tracks. That is, we sought to avoid special techniques, and did not apply any explicit or implicit query classifiers. The system was designed to be scalable and efficient.

Bibtex 
@inproceedings{DBLP:conf/trec/AnhM04,
    author = {Vo Ngoc Anh and Alistair Moffat},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Melbourne University 2004: Terabyte and Web Tracks},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/umelbourne.tera.web.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/AnhM04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Novel Approaches in Text Information Retrieval - Experiments in the Web Track of TREC 2004

Mohamed Farah, Daniel Vanderpooten

Abstract

In this paper, we report our experiments in the mixed query task of the Web track for TREC 2004. We deal with the problem of ranking Web documents within a multicriteria framework and propose a novel approach for information retrieval. We focus on the design of a set of criteria aiming at capturing complementary aspects of relevance. Moreover, we provide aggregation procedures that are based on decision rules, to get the ranking of relevant documents.

Bibtex 
@inproceedings{DBLP:conf/trec/FarahV04,
    author = {Mohamed Farah and Daniel Vanderpooten},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Novel Approaches in Text Information Retrieval - Experiments in the Web Track of {TREC} 2004},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/lamsade.web.pdf},
    timestamp = {Thu, 21 Jan 2021 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/FarahV04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Language Models for Searching in Web Corpora

Jaap Kamps, Gilad Mishne, Maarten de Rijke

Abstract

We describe our participation in the TREC 2004 Web and Terabyte tracks. For the web track, we employ mixture language models based on document full-text, incoming anchor-text, and documents titles, with a range of web-centric priors. We provide a detailed analysis of the effect on relevance of document length, URL structure, and link topology. The resulting web-centric priors are applied to three types of topics—distillation, home page, and named page—and improve effectiveness for all topic types, as well as for the mixed query set. For the terabyte track, we experimented with building an index just based on the document titles, or on the incoming anchor texts. Very selective indexing leads to a compact index that is effective in terms of early precision, catering for the typical web searcher behavior

Bibtex 
@inproceedings{DBLP:conf/trec/KampsMR04,
    author = {Jaap Kamps and Gilad Mishne and Maarten de Rijke},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Language Models for Searching in Web Corpora},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/uamsterdam.web.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/KampsMR04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Finding "Abstract Fields" of Web Pages and Query Specific Retrieval - THUIR at TREC 2004 Web Track

Yiqun Liu, Canhui Wang, Min Zhang, Shaoping Ma

Abstract

In this year's TREC Web Track research, THUIR participated in the Mixed-query Task. This task involves a single query set comprising 3 kinds of queries (Homepage Finding, Named Page Finding and Topic distillation) which are mixed and unlabelled. Efforts have been made on two directions: to find a strong and robust unified approach which works well for all kinds of queries, and to build a query-specific retrieval strategy that classifies queries by types and perform specific approaches. The using of non-content information has been studied in both approaches. With topic distillation and navigational search tasks in the last year, we are able to build a training set with 150 topics and corresponding relevant qrels. This training set is used to evaluate effectiveness of different methods in mixed query search. Experiments in section 2, 3 and 4 are all based on this set.

Bibtex 
@inproceedings{DBLP:conf/trec/LiuWZM04,
    author = {Yiqun Liu and Canhui Wang and Min Zhang and Shaoping Ma},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Finding "Abstract Fields" of Web Pages and Query Specific Retrieval - {THUIR} at {TREC} 2004 Web Track},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/tsinghua-ma.web.pdf},
    timestamp = {Wed, 16 Sep 2020 01:00:00 +0200},
    biburl = {https://dblp.org/rec/conf/trec/LiuWZM04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

SJTU at TREC 2004: Web Track Experiments

Yiming Lu, Jian Hu, Fanyuan Ma

Abstract

This is the first year our lab to participate in Trec. We participate in Mixed-Query task for the Web track. All the runs we submitted are based on the modified Okapi weighting scheme. Besides, we used several heuristics as the re-rank method: site-merging, minimal span weight, and etc. Also, the PageRank of a document is combined with the similarity of the document with the query to obtain an overall ranking of documents. Especially for the mixed-query task, we try a simple classification method to estimate whether the query is topic distillation or entry-page finding.

Bibtex 
@inproceedings{DBLP:conf/trec/LuHM04,
    author = {Yiming Lu and Jian Hu and Fanyuan Ma},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {{SJTU} at {TREC} 2004: Web Track Experiments},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/shanghaiu.web.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/LuHM04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Towards Grid-Based Information Retrieval

Gregory B. Newby

Abstract

The IRTools software toolkit was used in TREC 2004 for submissions to the Web track and the Terabyte track. Terabyte track results were not available at the time of the due date for this Proceedings paper. While Web track results were available, qrels were not. Because we discovered a bug in the MySQL++ API that truncated docid numbers in our results, we will await qrels to reevaluate submitted runs and report results. This year, the Terabyte track dictated some changes to IRTools in order to handle the 430+GB of text (about 25M documents). The main change was to operate on chunks of the collection (272 separate chunks, each containing one of the Terabyte collections' subdirectories). Chunks were generated in parallel using the National Center for Supercomputing Application's cluster, Mercury (dual Itanium systems). Up to about 40 systems were used simultaneously for both indexing and querying. Query merging was simplistic, based on the cosine value with Lnu.Ltc weighting. Use of the NCSA cluster, and other experiments with commodity clusters, is part of work underway to enable information retrieval in Grid computing environments. The site http://www.gir-wg.org has information about Grid Information Retrieval (GIR), including links to the published Requirements document and draft Architecture document. The GIR working group is chartered by the Global Grid Forum (GGF) to develop standards and reference implementations for GIR. TREC participants are urged to consider getting involved with Grid computing. Computational grids offer a very good fit for the needs of large-scale information retrieval research and practice. This brief abstract for the proceedings will be replaced with a complete analysis of this year's submissions for the full conference paper. Meanwhile, Newby (2004) provides a profile of IRTools, which is generally applicable to this year's submissions.

Bibtex 
@inproceedings{DBLP:conf/trec/Newby04,
    author = {Gregory B. Newby},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Towards Grid-Based Information Retrieval},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/ualaska.web.tera.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/Newby04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

University of Glasgow at TREC 2004: Experiments in Web, Robust, and Terabyte Tracks with Terrier

Vassilis Plachouras, Ben He, Iadh Ounis

Abstract

With our participation in TREC2004, we test Terrier, a modular and scalable Information Retrieval framework, in three tracks. For the mixed query task of the Web track, we employ a decision mechanism for selecting appropriate retrieval approaches on a per-query basis. For the robust track, in order to cope with the poorly-performing queries, we use two pre-retrieval performance predictors and a weighting function recommender mechanism. We also test a new training approach for the automatic tuning of the term frequency normalisation parameters. In the Terabyte track, we employ a distributed version of Terrier and test the effectiveness of techniques, such as using the anchor text, query expansion and selecting an optimal weighting model for each query. Overall, in all three tracks we participated, Terrier and the tested Divergence From Randomness models were shown to be stable and effective.

Bibtex 
@inproceedings{DBLP:conf/trec/PlachourasHO04,
    author = {Vassilis Plachouras and Ben He and Iadh Ounis},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {University of Glasgow at {TREC} 2004: Experiments in Web, Robust, and Terabyte Tracks with Terrier},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/uglasgow.web.robust.tera.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/PlachourasHO04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Microsoft Research Asia at Web Track and Terabyte Track of TREC 2004

Ruihua Song, Ji-Rong Wen, Shuming Shi, Guomao Xin, Tie-Yan Liu, Tao Qin, Xin Zheng, Jiyu Zhang, Gui-Rong Xue, Wei-Ying Ma

Abstract

Here we report Microsoft Research Asia (MSRA)'s experiments on the mixed query task of Web track and Terabyte track at TREC 2004. For Web track, we mainly test a set of new technologies. One of our efforts is to test some new features of Web pages to see if they are helpful to retrieval performance. Title extraction, sitemap based feature propagation, and URL scoring are of this kind. Another effort is to propose new function or algorithm to improve relevance or importance ranking. For example, we found that a new link analysis algorithm named HostRank that can outweigh PageRank [4] for topic distillation queries based on our experimental results. Eventually, linear combination of multiple scores with normalizations is tried to achieve stable performance improvement with mixed queries.

Bibtex 
@inproceedings{DBLP:conf/trec/SongWSXLQZZXM04,
    author = {Ruihua Song and Ji{-}Rong Wen and Shuming Shi and Guomao Xin and Tie{-}Yan Liu and Tao Qin and Xin Zheng and Jiyu Zhang and Gui{-}Rong Xue and Wei{-}Ying Ma},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Microsoft Research Asia at Web Track and Terabyte Track of {TREC} 2004},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/microsoft-asia.web.tera.pdf},
    timestamp = {Tue, 01 Dec 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/SongWSXLQZZXM04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Meiji University Web, Novelty and Genomic Track Experiments

Tomoe Tomiyama, Kosuke Karoji, Takeshi Kondo, Yuichi Kakuta, Tomohiro Takagi

Abstract

We participated in Novelty track, the topic distillation task of Web track and ad hoc task of Genomic Track. Our main challenge is to deal with meaning of words and improve retrieval performance.

Bibtex 
@inproceedings{DBLP:conf/trec/TomiyamaKKKT04,
    author = {Tomoe Tomiyama and Kosuke Karoji and Takeshi Kondo and Yuichi Kakuta and Tomohiro Takagi},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Meiji University Web, Novelty and Genomic Track Experiments},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/meijiu.web.novelty.geo.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/TomiyamaKKKT04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Robust, Web and Terabyte Retrieval with Hummingbird SearchServer at TREC 2004

Stephen Tomlinson

Abstract

Hummingbird participated in 3 tracks of TREC 2004: the ad hoc task of the Robust Retrieval Track (find at least one relevant document in the first 10 rows from 1.9GB of news and government data), the mixed navigational and distillation task of the Web Track (find the home or named page or key resource pages in 1.2 million pages (18GB) from the .GOV domain), and the ad hoc task of the Terabyte Track (find all the relevant documents with high precision from 25.2 million pages (426GB) from the .GOV domain). In the robustness task, SearchServer found a relevant document in the first 10 rows for 46 of the 49 new short (Title-only) topics. In the web task, SearchServer returned a desired page in the first 10 rows for more than 75% of the 225 queries. In the terabyte task, SearchServer found a relevant document in the first 10 rows for 45 of the 49 short topics.

Bibtex 
@inproceedings{DBLP:conf/trec/Tomlinson04,
    author = {Stephen Tomlinson},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Robust, Web and Terabyte Retrieval with Hummingbird SearchServer at {TREC} 2004},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/humingbird.robust.web.tera.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/Tomlinson04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

WIDIT in TREC 2004 Genomics, Hard, Robust and Web Tracks

Kiduk Yang, Ning Yu, Adam Wead, Gavin La Rowe, Yu-Hsiu Li, Christopher Friend, Yoon Lee

Abstract

To facilitate understanding of information as well as its discovery, we need to combine the capabilities of the human and the machine as well as multiple methods and sources of evidence. Web Information Discovery Tool (WIDIT) Laboratory at the Indiana University School of Library and Information Science houses several projects that aim to apply this idea of multi-level fusion in the areas of information retrieval and knowledge organization. The TREC research group of WIDIT, who engages in examination of information retrieval strategies that can accommodate a variety of data environments and search tasks, participated in the Genomics, HARD, Robust, and Web tracks in TREC-2004. The basic approach of WIDIT was to leverage multiple sources of evidence, combine multiple methods, and integrate the strengths of man and the machine. Our main strategies for the tracks were: the use of gene name thesaurus in the Genomics track; query expansion and relevance feedback in the HARD track; query expansion with keywords from Web search in the Robust track, and the interactive system tuning process called “Dynamic Tuning” in the Web track.

Bibtex 
@inproceedings{DBLP:conf/trec/YangYWRLFL04,
    author = {Kiduk Yang and Ning Yu and Adam Wead and Gavin La Rowe and Yu{-}Hsiu Li and Christopher Friend and Yoon Lee},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {{WIDIT} in {TREC} 2004 Genomics, Hard, Robust and Web Tracks},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/indianau.geo.hard.robust.web.pdf},
    timestamp = {Tue, 24 Nov 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/YangYWRLFL04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

Microsoft Cambridge at TREC 13: Web and Hard Tracks

Hugo Zaragoza, Nick Craswell, Michael J. Taylor, Suchi Saria, Stephen E. Robertson

Abstract

All our submissions from the Microsoft Research Cambridge (MSRC) team this year continue to explore issues in IR from a perspective very close to that of the original Okapi team, working first at City University of London, and then at MSRC. A summary of the contributions by the team, from TRECs 1 to 7 is presented in [3]. In this work, weighting schemes for ad-hoc retrieval were developed, inspired by a probabilistic interpretation of relevance; this lead, for instance, to the successful BM25 weighting function. These weighting schemes were extended to deal with pseudo relevance feedback (blind feedback). Furthermore, the Okapi team participated in most of the early interactive tracks, and also developed iterative relevance feedback strategies for the routing task. Following up on the routing work, TRECs 7-11 submissions dealt principally with the adaptive filtering task; this work is summarised in [5]. Last year MSRC entered only the HARD track, concentrating on the use of the clarification forms [6]. We hoped to make use of the query expansion methods developed for filtering in the context of feedback on snippets in the clarification forms. However, our methods were not very successful. In this year's TREC we took part in the HARD and WEB tracks. In HARD, we tried some variations on the process of feature selection for query expansion. On the WEB track, we investigated the combination of information from different content fields and from link-based features. Section 3 briefly describes the system we used. Section 4 describes our HARD participation and Section 5 our TREC participation.

Bibtex 
@inproceedings{DBLP:conf/trec/ZaragozaCTSR04,
    author = {Hugo Zaragoza and Nick Craswell and Michael J. Taylor and Suchi Saria and Stephen E. Robertson},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {Microsoft Cambridge at {TREC} 13: Web and Hard Tracks},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/microsoft-cambridge.web.hard.pdf},
    timestamp = {Tue, 04 May 2021 01:00:00 +0200},
    biburl = {https://dblp.org/rec/conf/trec/ZaragozaCTSR04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}

TREC 2004 Web Track Experiments at CAS-ICT

Zhaotao Zhou, Yan Guo, Bin Wang, Xueqi Cheng, Hongbo Xu, Gang Zhang

Abstract

This report presents CAS-ICT's experiments on the Mixed query task of the TREC2004 Web track. Our work focused on combining different Web page evidences together to improve the overall retrieval performance. Four kinds of evidences, including body content(C), anchor texts (AT), basic structural information (S0) and extended structural information (S1) were considered for retrieval. Six combination functions were investigated in our experiments. The experimental results show that most functions can improve the retrieval performance. Some heuristic re-ranking techniques were also introduced and tested in the task. No query classification was made during the experiments. Keywords: Web retrieval, TREC 2004, the Mixed query task, information fusion.

Bibtex 
@inproceedings{DBLP:conf/trec/ZhouGWCXZ04,
    author = {Zhaotao Zhou and Yan Guo and Bin Wang and Xueqi Cheng and Hongbo Xu and Gang Zhang},
    editor = {Ellen M. Voorhees and Lori P. Buckland},
    title = {{TREC} 2004 Web Track Experiments at {CAS-ICT}},
    booktitle = {Proceedings of the Thirteenth Text REtrieval Conference, {TREC} 2004, Gaithersburg, Maryland, USA, November 16-19, 2004},
    series = {{NIST} Special Publication},
    volume = {500-261},
    publisher = {National Institute of Standards and Technology {(NIST)}},
    year = {2004},
    url = {http://trec.nist.gov/pubs/trec13/papers/cas.ict.web.pdf},
    timestamp = {Thu, 12 Mar 2020 00:00:00 +0100},
    biburl = {https://dblp.org/rec/conf/trec/ZhouGWCXZ04.bib},
    bibsource = {dblp computer science bibliography, https://dblp.org}
}