OpenRaiser/Intern-Atlas huggingface dataset:
Improving Two-Stage Ad-Hoc Retrieval for Short Queries
Authors: K. L. Kwok, M. Chan
Venue: SIGIR
Year: 1998

Article Improving two-stage ad-hoc retrieval for short queries Share on Authors: K. L. Kwok Computer Science Department, Queens College, CUNY, Flushing, NY Computer Science Department, Queens College, CUNY, Flushing, NYView Profile , M. Chan Computer Science Department, Queens College, CUNY, Flushing, NY Computer Science Department, Queens College, CUNY, Flushing, NYView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 250–256https://doi.org/10.1145/290941.291003Online:01 August 1998Publication History 40citation553DownloadsMetricsTotal Citations40Total Downloads553Last 12 Months13Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
Comparing Interactive Information Retrieval systems Across Sites: The TREC-6 Interactive Track Matrix Experiment
Authors: Eric Lagergren, Paul Over
Venue: SIGIR
Year: 1998

Article Free Access Share on Comparing interactive information retrieval systems across sites: the TREC-6 interactive track matrix experiment Authors: Eric Lagergren Statistical Engineering Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD Statistical Engineering Division, National Institute of Standards and Technology (NIST), Gaithersburg, MDView Profile , Paul Over Information Access and User Interfaces Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD Information Access and User Interfaces Division, National Institute of Standards and Technology (NIST), Gaithersburg, MDView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 164–172https://doi.org/10.1145/290941.290986Online:01 August 1998Publication History 43citation637DownloadsMetricsTotal Citations43Total Downloads637Last 12 Months10Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Using a Generalized Instance Set for Automatic Text Categorization
Authors: Wai Lam, Chao Yang Ho
Venue: SIGIR
Year: 1998

Article Free Access Share on Using a generalized instance set for automatic text categorization Authors: Wai Lam Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong KongView Profile , Chao Yang Ho Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong Kong Department of Systems Engineering and Engineering Management, The Chinese University of Hong Kong, Shatin, Hong KongView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 81–89https://doi.org/10.1145/290941.290961Published:01 August 1998Publication History 121citation930DownloadsMetricsTotal Citations121Total Downloads930Last 12 Months22Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
Extracting Classification Knowledge of Internet Documents with Mining Term Associations: A Semantic Approach
Authors: Shian-Hua Lin, Chi-Sheng Shih, Meng Chang Chen, Jan-Ming Ho, Ming-Tat Ko, Yueh-Ming Huang
Venue: SIGIR
Year: 1998

In this paper, we present a system that extracts and generalizes terms from Internet documents to represent classification knowledge of a given class hierarchy. We propose a measurement to evaluate the importance of a term with respect to a class in the class hierarchy, and denote it as support. With a given threshold, terms with high supports are sifted as keywords of a class, and terms with low supports are filtered out. To further enhance the recall of this approach, Mining Association Rules technique is applied to mine the association between terms. An inference model is composed of these association relations and the previously computed supports of the terms in the class. To increase the recall rate of the keyword selection process. we then present a polynomialtime inference algorithm to promote a term, strongly associated to a known keyword, to a keyword. According to our experiment results on the collected Internet documents from Yam search engine, we show that the proposed methods In the paper contribute to refine the classification knowledge and increase the recall of keyword selection.
Predicting Query Times
Authors: Rodger J. McNab, Yong Wang, Ian H. Witten, Carl Gutwin
Venue: SIGIR
Year: 1998

We outline the need for search engines to provide user feedback on the expected time for a query, describe a scheme for learning a model of query time by observing sample queries, and discuss the results obtained for a set of actual user queries on a document collection using the MG search engine.
Fast Searching on Compressed Text Allowing Errors
Authors: Edleno Silva de Moura, Gonzalo Navarro, Nivio Ziviani, Ricardo A. Baeza-Yates
Venue: SIGIR
Year: 1998

We present a fast compression and decompression scheme for natural language texts that allows efficient and flexible string matching by searching the compressed text directly. The compression scheme uses a word-based Huffman encoding and the coding alphabet is byte-oriented rather than bit-oriented. We compress typical English texts to about 30% of their original size, against 40% and 35% for Compress and Gaip, respectively. Compression times are close to the times of Compress and approximately half the times of Gzip, and decompression times are lower than those of Gzip and one third of those of Compress. The searching algorithm allows a large number of variations of the exact and approximate compressed string matching problem, such as phrases, ranges, complements, wild cards and arbitrary regular expressions. Separators and stopwords can be discarded at search time without significantly increasing the cost. The algorithm is based on a word-oriented shift-or algorithm and a fast Boyer-Moore-type filter. It concomitantly uses the vocabulary of the text available as part of the Huffman coding data. When searching for simple patterns, our experiments show that running our algorithm on a compressed text is twice as fast as running Agrep on the uncompressed version of the same text. When searching complex or approximate patterns, our algorithm is up to 8 times faster than Agrep. We also mention the impact of our technique in inverted files pointing to documents or logical blocks as Glimpse.
A Flexible Model for Retrieval of SGML Documents
Authors: Sung-Hyon Myaeng, Don-Hyun Jang, Mun-Seok Kim, Zong-Cheol Zhoo
Venue: SIGIR
Year: 1998

Abstract In traditional information retrieval (IR) systems, a document as a whole is the target for a query. With increasing interests in structured documents like SGML documents, there is a growing need to build an LR system that can retrieve parts of documents, which satisfy not only content-based but also structure-based requirements. In this paper, we describe an inference-net-based approach to this problem. The model is capable of retrieving elements at any level in a principled way, satisfying certain containment constraints in a quety. Moreover, lvhile the model is general enough to reproduce the ranking strategy adopted by conventional document retrieval systems by making use of document and collection level statistics such as TF and IDF, its flexibility allows for incorporation of a variety of pragmatic and semantic information associated with document structures. We implemented the model and ran a series of experiments to show that, in addition to the added functionality, the use of the structural information embedded in SGML documents can improve the effectiveness of document retrieval, compared to the case where no such information is used. We also show that giving a pragmatic preference to a certain element tape of the SGML documents can enhance retrieval effectiveness. 1
Modeling and Combining Evidence Provided by Document Relationships Using Probabilistic Argumentation Systems
Authors: Justin Picard
Venue: SIGIR
Year: 1998

Previous research has shown that hypertext links may be a useful source of evidence for document contents and relevance, but these evidence are rather difficult to represent and combine. This paper introduces a new and sound model for representing and handling hypertext links in IR. This model is based on ctProbabilistic Argumentation Systems )), a technique which combines logic and probability to handle uncertainty. Some experiments show the potential of this approach, which requires no ad-hoc parameters.
The Effects of Query Structure and Dictionary Setups in Dictionary-Based Cross-Language Information Retrieval
Authors: Ari Pirkola
Venue: SIGIR
Year: 1998

this paper, the translation polysemy and the dictionary coverage problems were attacked by means of the combination of a general language MRD and a domain specific MR D i.e., a medical dictionary. The domain was restricted to medicine and health by choosing as test requests TREC&apos;s (see Harman, 1996) health related topics. The performance of translated Finnish queries against English documents was compared to the performance of original English queries against English documents. Because the domain was medicine and health, it was assumed that the medical dictionary disambiguates word senses, giving less incorrect senses than the general dictionary, and that it contains such search keys that are not found in the general dictionary
A Language Modeling Approach to Information Retrieval
Authors: Jay M. Ponte, W. Bruce Croft
Venue: SIGIR
Year: 1998

Article A language modeling approach to information retrieval Share on Authors: Jay M. Ponte Computer Science Department, University of Massachusetts, Amherst Computer Science Department, University of Massachusetts, AmherstView Profile , W. Bruce Croft Computer Science Department, University of Massachusetts, Amherst Computer Science Department, University of Massachusetts, AmherstView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 275–281https://doi.org/10.1145/290941.291008Online:01 August 1998Publication History 1,592citation7,260DownloadsMetricsTotal Citations1,592Total Downloads7,260Last 12 Months258Last 6 weeks34 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
A Cognitive Model for Searching for Ill-Defined Targets on the Web: The Relationship Between Search Strategies and User Satisfaction
Authors: Mari Saito, Kazunori Ohmura
Venue: SIGIR
Year: 1998

We performed an experiment in which subjects were asked to find a gift for a friend using the Web. The subjects were divided into two groups, only one of which was instructed to form a mental image prior to the search. We found that subjects who formed a prior mental image took longer to complete their search and also reported higher degrees of satisfaction with their search result. We present a cognitive model in which the search takes place as an incremental refinement of search target candidates and their attributes.
Boosting and Rocchio Applied to Text Filtering
Authors: Robert E. Schapire, Yoram Singer, Amit Singhal
Venue: SIGIR
Year: 1998

We discuss two learning algorithms for text filtering: modified Rocchio and a boosting algorithm called AdaBoost. We show how both algorithms can be adapted to maximize any general utility matrix that associates cost (or gain) for each pair of machine prediction and correct label. We first show that AdaBoost significantly outperforms another highly effective text filtering algorithm. We then compare AdaBoost and Rocchio over three large text filtering tasks. Overall both algorithms are comparable and are quite effective. AdaBoost produces better classifiers than Rocchio when the training collection contains a very large number of relevant documents. However, on these tasks, Rocchio runs much faster than AdaBoost. 1 Introduction With the explosion in the amount of information available electronically, information filtering systems that automatically send articles of potential interest to a user are becoming increasingly important. If users indicate their interests to a filtering system...
Aspect Windows, 3-D Visualizations, and Indirect Comparisons of Information Retrieval Systems
Authors: Russell C. Swan, James Allan
Venue: SIGIR
Year: 1998

Abstract : We built two Information Retrieval systems that were targeted for the TREC-6 "aspect oriented" retrieval track. The systems were built to test the usefulness of different visualizations in an interactive IR setting-in particular, an "aspect window" for the chosen task, and a 3-D visualization of document inter-relationships. We studied 24 users of the system in order to investigate: whether the systems were more effective than a control system, whether experienced users outperformed novices, whether spatial reasoning ability was a good predictor of effective use of 3-D, and whether the systems could be compared indirectly via a control system. Our results show substantial differences in user performance are related to spatial reasoning ability and to a lesser degree other traits. We also obtained markedly different results from the direct and indirect comparisons.
Compressed Inverted Files with Reduced Decoding Overheads
Authors: Vo Ngoc Anh, Alistair Moffat
Venue: SIGIR
Year: 1998

Compressed inverted files are the most compact way of indexing large text databases, typically occupying around 10% of the space of the collection they index. The drawback of compression is the need to decompress the index lists during query processing. Here we describe an improved implementation of compressed inverted lists that eliminates almost all redundant decoding and allows extremely fast processing of conjunctive Boolean queries and ranked queries. We also describe a pruning method to reduce the number of candidate documents considered during the evaluation of ranked queries. Experimental results with a database of 510 Mb show that the new mechanism can reduce the CPU and elapsed time for Boolean queries of 4-10 terms to one tenth and one fifth respectively of the standard technique. For ranked queries, the new mechanism reduces both CPU and elapsed time to one third and memory usage to less than one tenth of the standard algorithm, with no degradation in retrieval effectiveness. 1
Predicting the Performance of Linearly Combined IR Systems
Authors: Christopher C. Vogt, Garrison W. Cottrell
Venue: SIGIR
Year: 1998

We introduce a new technique for analyzing combination models. The technique allows us to make qualitative conclusions about which IR systems should be combined. We achieve this by using a linear regression to accurately (T ' = 0.98) predict the performance of the combined system based on quantitative measurements of individual component systems taken from TREC5. When applied to a linear model (weighted sum of relevance scores), the technique supports several previously suggested hypotheses: one should maximize both the individual systems' performances and the overlap of relevant documents between systems, while minimizing the overlap of nonrelevant documents. It also suggests new conclusions: both systems should distribute scores similarly, but not rank relevant documents similarly. It furthermore suggests that the linear model is only able to exploit a fraction of the benefit possible from combination. The technique is general in nature and capable of pointing out the strengths and weaknesses of any given combination approach.
Discovering Typical Structures of Documents: A Road Map Approach
Authors: Ke Wang, Huiqing Liu
Venue: SIGIR
Year: 1998

Article Discovering typical structures of documents: a road map approach Share on Authors: Ke Wang Department of Information Systems and Computer Science, National University of Singapore Department of Information Systems and Computer Science, National University of SingaporeView Profile , Huiqing Liu BioInformatics Center, National University of Singapore BioInformatics Center, National University of SingaporeView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 146–154https://doi.org/10.1145/290941.290982Online:01 August 1998Publication History 82citation642DownloadsMetricsTotal Citations82Total Downloads642Last 12 Months9Last 6 weeks2 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
New Techniques for Open-Vocabulary Spoken Document Retrieval
Authors: Martin Wechsler, Eugen Munteanu, Peter Schäuble
Venue: SIGIR
Year: 1998

Article Free Access Share on New techniques for open-vocabulary spoken document retrieval Authors: Martin Wechsler Swiss Federal Institute of Technology (ETH), Zürich Swiss Federal Institute of Technology (ETH), ZürichView Profile , Eugen Munteanu Swiss Federal Institute of Technology (ETH), Zürich Swiss Federal Institute of Technology (ETH), ZürichView Profile , Peter Schäuble Swiss Federal Institute of Technology (ETH), Zürich Swiss Federal Institute of Technology (ETH), ZürichView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998Pages 20–27https://doi.org/10.1145/290941.290950Published:01 August 1998Publication History 25citation640DownloadsMetricsTotal Citations25Total Downloads640Last 12 Months37Last 6 weeks3 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Publisher SiteeReaderPDF
Effective Retrieval with Distributed Collections
Authors: Jinxi Xu, James P. Callan
Venue: SIGIR
Year: 1998

This paper evaluates the retrieval effectiveness of distributed information retrieval systems in realistic environments. We find that when a large number of collections are available, the retrieval effectiveness is significantly worse than that of centralized systems, mainly because typical queries are not adequate for the purpose of choosing the right collections. We propose two techniques to address the problem. One is to use phrase information in the collection selection index and the other is query expansion. Both techniques enhance the discriminatory power of typical queries for choosing the right collections and hence significantly improve retrieval results. Query expansion, in particular, brings the effectiveness of searching a large set of distributed collections close to that of searching a centralized collection. 1 Introduction In today&apos;s network environments, information is highly distributed. The Internet or World Wide Web, for example, contains thousands of collections. ...
A Probabilitstic Solution to the Selection and Fusion Problem in Distributed Information Retrieval
Authors: Christoph Baumgarten
Venue: SIGIR
Year: 1999

A model for optimal information retrieval over a distributed document collection is described and experimentally evaluated. The fusion of retrieval results corresponding to document subcollections is performed according to the Probability Ranking Principle. Part of the model is a selection criterion for e ectively limiting the ranking process to a subset of subcollections.
A New Statistical Formula for Chinese Text Segmentation Incorporating Contextual Information
Authors: Yubin Dai, Teck Ee Loh, Christopher S. G. Khoo
Venue: SIGIR
Year: 1999

Article A new statistical formula for Chinese text segmentation incorporating contextual information Share on Authors: Yubin Dai Division of Information Studies, School of Applied Science, Nanyang Technological University, Singapore 639798 Division of Information Studies, School of Applied Science, Nanyang Technological University, Singapore 639798View Profile , Teck Ee Loh 10 Kent Ridge Crescent, Data Storage Institute, Singapore 119260 10 Kent Ridge Crescent, Data Storage Institute, Singapore 119260View Profile , Christopher S. G. Khoo Division of Information Studies, School of Applied Science, Nanyang Technological University, Singapore 639798 Division of Information Studies, School of Applied Science, Nanyang Technological University, Singapore 639798View Profile Authors Info & Claims SIGIR '99: Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrievalAugust 1999 Pages 82–89https://doi.org/10.1145/312624.312659Online:01 August 1999Publication History 17citation864DownloadsMetricsTotal Citations17Total Downloads864Last 12 Months10Last 6 weeks0 Get Citation AlertsNew Citation Alert added!This alert has been successfully added and will be sent to:You will be notified whenever a record that you have chosen has been cited.To manage your alert preferences, click on the button below.Manage my AlertsNew Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteGet Access
From Reading to Retrieval: Freeform Ink Annotations as Queries
Authors: Gene Golovchinsky, Morgan N. Price, Bill N. Schilit
Venue: SIGIR
Year: 1999

User interfaces for digital libraries tend to focus on retrieval: users retrieve documents online, but then print them out and work with them on paper. One reason for printing documents is to annotate them with freeform ink while reading. Annotation can help readers to understand documents and to make them their own. In addition, annotation can reveal readers' interests with respect to a particular document. In particular, it is possible to construct full-text queries based on annotated passages of documents. We describe an experiment that tested the effectiveness of such queries, as compared to relevance feedback query techniques. For a set of TREC topics and documents, queries derived from annotated passages produced significantly better results than queries derived from subjects' judgments of relevance.