OpenRaiser/Intern-Atlas huggingface dataset:
Comparing Representations in Chinese Information Retrieval
Authors: K. L. Kwok
Venue: SIGIR
Year: 1997

Three representation methods are empirically investigated for Chinese information retrieval: 1-gram (single character), bigram (two contiguous overlapping characters), and short-word indexing based on a simple segmentation of the text. The retrieval collection is the approximately 170 MB TREC-5 Chinese corpus of news articles, and 28 queries that are long and rich in wordings. Evaluation shows that 1-gram indexing is good but not sufficiently competitive, while bigram indexing works surprisingly well. Bigram indexing leads to a large index term space, three times that of short-word indexing, but is as good as short-word indexing in precision, and about 5% better in relevants retrieved. The best average non-interpolated precision is about 0.45, 17% better than 1-gram indexing and quite high for a mainly statistical approach. 1. Introduction While information retrieval (IR) in English has over thirty years of history, IR in Chinese is relatively recent. It is well-known that written Chi...
Dempster-Shafer's Theory of Evidence Applied to Structured Documents: Modelling Uncertainty
Authors: Mounia Lalmas
Venue: SIGIR
Year: 1997

article Free Access Share on Dempster-Shafer's theory of evidence applied to structured documents: modelling uncertainty Author: Mounia Lalmas Department of Computing Science, University of Glasgow, G12 8QQ Scotland Department of Computing Science, University of Glasgow, G12 8QQ ScotlandView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SIDecember 1997 pp 110–118https://doi.org/10.1145/278459.258546Published:01 July 1997Publication History 56citation1,216DownloadsMetricsTotal Citations56Total Downloads1,216Last 12 Months13Last 6 weeks1 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 Alerts New Citation Alert!Please log in to your account Save to BinderSave to BinderCreate a New BinderNameCancelCreateExport CitationPublisher SiteeReaderPDF
The Potential and Actual Effectiveness of Interactive Query Expansion
Authors: Mark Magennis, C. J. van Rijsbergen
Venue: SIGIR
Year: 1997

article Free AccessThe potential and actual effectiveness of interactive query expansion Authors: Mark Magennis Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United Kingdom Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United KingdomView Profile , Cornelis J. van Rijsbergen Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United Kingdom Department of Computing Science, University of Glasgow, Glasgow G12 8QQ, United KingdomView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SIDecember 1997 pp 324–332https://doi.org/10.1145/278459.258603Published:01 July 1997Publication History 74citation957DownloadsMetricsTotal Citations74Total Downloads957Last 12 Months33Last 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
Exploration of Text Collections with Hierarchical Feature Maps
Authors: Dieter Merkl
Venue: SIGIR
Year: 1997

Document classification is one of the central issues in information retrieval research. The aim is to uncover similarities between text documents. In other words, classification techniques are used to gain insight in the structure of the various data items contained in the text archive. In this paper we show the results from using a hierarchy of self-organizing maps to perform the text classification task. Each of the individual self-organizing maps is trained independently and gets specialized to a subset of the input data. As a consequence, the choice of this particular artificial neural network model enables the true establishment of a document taxonomy. The benefit of this approach is a straightforward representation of document similarities combined with dramatically reduced training time. In particular, the hierarchical representation of document collections is appealing because it is the underlying organizational principle in use by librarians providing the necessary familiarity...
Feature Selection, Perceptron Learning, and a Usability Case Study for Text Categorization
Authors: Hwee Tou Ng, Wei Boon Goh, Kok Leong Low
Venue: SIGIR
Year: 1997

article Free AccessFeature selection, perceptron learning, and a usability case study for text categorization Authors: Hwee Tou Ng DSO National Laboratories, 20 Science Park Drive, Singapore DSO National Laboratories, 20 Science Park Drive, SingaporeView Profile , Wei Boon Goh Ministry of Defence, Gombak Drive Ministry of Defence, Gombak DriveView Profile , Kok Leong Low Ministry of Defence, Gombak Drive Ministry of Defence, Gombak DriveView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SI01 July 1997pp 67–73https://doi.org/10.1145/278459.258537Published:01 July 1997Publication History 253citation2,706DownloadsMetricsTotal Citations253Total Downloads2,706Last 12 Months148Last 6 weeks14 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
Overlapping Statistical Word Indexing: A New Indexing Method for Japanese Text
Authors: Yashishi Ogawa, Toru Matsuda
Venue: SIGIR
Year: 1997

article Free AccessOverlapping statistical word indexing: a new indexing method for Japanese text Authors: Yasushi Ogawa Information and Communication R&D Center, RICOH Co., Ltd., 3-2-3 Shin-yokohama, Kouhoku-ku, Yokohama, Kanagawa 222, Japan Information and Communication R&D Center, RICOH Co., Ltd., 3-2-3 Shin-yokohama, Kouhoku-ku, Yokohama, Kanagawa 222, JapanView Profile , Toru Matsuda Information and Communication R&D Center, RICOH Co., Ltd., 3-2-3 Shin-yokohama, Kouhoku-ku, Yokohama, Kanagawa 222, Japan Information and Communication R&D Center, RICOH Co., Ltd., 3-2-3 Shin-yokohama, Kouhoku-ku, Yokohama, Kanagawa 222, JapanView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SIDecember 1997 pp 226–234https://doi.org/10.1145/278459.258576Published:01 July 1997Publication History 15citation531DownloadsMetricsTotal Citations15Total Downloads531Last 12 Months18Last 6 weeks1 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
Image Retrieval by Appearance
Authors: Srinivas Ravela, R. Manmatha
Venue: SIGIR
Year: 1997

A system to retrieve images using a syntactic description of appearance is presented. A multi-scale invariant wxtor representation is obtained by first filtering images in the database with Gaussian derivative filters at several acalea and then computing low order differential invariants. The multi-scale representation is indexed for rapid retrieval. Queries are designed by the users horn an example image by eelecting appropriate regions. The invariant xnxtors corrmponding to these regions are matched with those in the database both in feature space as well M in coordinate space and a match score is obtained for each image. The results are then displayed to the user sorted by the match score. I?kom experiments conducted with ovsr 1500 images it is shown that imagee similar in appearance and whose viewpoint is within 25 degrees of the query image can be retrieved with an average precision of 57% 1 Introduction
Users Lost: Reflections on the Past, Future, and Limits of Information Science (Summary)
Authors: Tefko Saracevic
Venue: SIGIR
Year: 1997

article Free AccessUsers lost (summary): reflections on the past, future, and limits of information science Author: Tafko Saracevic School of Communication, Information and Library Studies, Rutgers University, 4 Huntington Street, New Brunswick, NJ School of Communication, Information and Library Studies, Rutgers University, 4 Huntington Street, New Brunswick, NJView Profile Authors Info & Claims ACM SIGIR ForumVolume 31Issue SI01 July 1997pp 1–2https://doi.org/10.1145/278459.258526Published:01 July 1997Publication History 2citation359DownloadsMetricsTotal Citations2Total Downloads359Last 12 Months11Last 6 weeks1 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
Projections for Efficient Document Clustering
Authors: Hinrich Schütze, Craig Silverstein
Venue: SIGIR
Year: 1997

Clustering is increasing in importance, but linear-and even constant-time clustering algorithms are often too slow for real-time applications. A simple way to speed up clustering is to speed up the distance calculations at the heart of clustering routines. We study two techniques for improving the cost ofdistance calculations, LSI and trrmcation, and determine both how much these techniques speed up clustering and how much they affect the quality of the resulting clusters. We find that the speed increase is significant whilesurprisingly -the quality of clustering is not adversely affected. We conclude that truncation yields clusters as good as those produced by full-profile clustering while offering a significant speed advantage.
Cross Language Speech Retrieval: Establishing a Baseline Performance
Authors: Paraic Sheridan, Martin Wechsler, Peter Schäuble
Venue: SIGIR
Year: 1997

We present here the realisation of cross-language speech retrieval system which retrieves German speech documents in response to user queries specified as French text. This has been achieved through the integration of two existing modules of the SPIDER information retrieval system, namely the query pseudo-translation module and the speech retrieval module. In the process of integrating these modules for cross-language speech retrieval, we have also made improvements to each in turn. We have progressed our research on aligning comparable corpora, an important resource for training the similarity thesauri used in our query pseudo-translation module, and we have now encorporated an automatic refinement loop into our speech retrieval module, using a probabilistic matching approach that has been proven effective in retrieving error-prone documents. We have also introduced the use of automatic relevance feedback for query expansion and tested this both as a refinement to automatically pseudo...
Almost-Constant-Time Clustering of Arbitrary Corpus Subsets
Authors: Craig Silverstein, Jan O. Pedersen 0001
Venue: SIGIR
Year: 1997

Methods exist for comtant-time clustering of corpus subsets selected via Scatter/Gather browsing [3]. In thii paper we expand on those techniqum, giving an algorithm for alrnostconstant-time clustering of arbitrary corpus subsets. This algorithm is never slower than clustering the document set from scratch, and for medium-sised and large sets it is significantly faster. ThE algorithm ia USSM for clustering arbitrary subsets of large corpora -obtained, for instance, by a boolean search -quickly enough to be useful in an interactive setting.
A Method for Monolingual Thesauri Merging
Authors: Marios Sintichakis, Panos Constantopoulos
Venue: SIGIR
Year: 1997

Thesauri merging is the activity of consolidating a set of thesauri into a thesaurus which accommodates the vocabularies and the structure of all thesauri being merged. In this paper, we introduce a general framework for monolingual thesauri merging. We also present a domain independent set-theoretic model for the representation of terms, relationships, and integrity constraints. Finally, we present a method for the merging of monolingual thesauri focusing on its mechanisms for the detection of equivalent terms among the thesauri being merged. Our method expands previous work on the problem; we introduce equivalence assumptions that express similarity between terms and we propose a term distance model which can be used to guide the confirmation or rejection of equivalence assumptions.
Effectiveness of a Graphical Display of Retrieval Results
Authors: Aravindan Veerasamy, Russell Heikes
Venue: SIGIR
Year: 1997

We present the design of a visualization tool that graphically displays the strength of query concepts in the retrieved documents. Graphically displaying document surrogate information enables set-at-a-time perusal of documents, rather than document-at-a-time perusal of textual displays. By prvialing additional relevance information about the retrieved documents, the tool aids the user in accurately identifying relevant documents. Results of an experiment evaluating the tool shows that when users have the tool they are able to identify relevant documents in a shorter period of time than without the tool, and with increased accuracy. We have evidence to believe that appropriately designed graphical displays can enable users to better interact with the system.
On-Line New Event Detection and Tracking
Authors: James Allan, Ron Papka, Victor Lavrenko
Venue: SIGIR
Year: 1998

Article On-line new event detection and tracking Share on Authors: James Allan Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MA Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MAView Profile , Ron Papka Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MA Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MAView Profile , Victor Lavrenko Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MA Center for Intelligent Information Retrieval, Computer Science Department, University of Massachusetts, Amherst, MAView Profile Authors Info & Claims SIGIR '98: Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrievalAugust 1998 Pages 37–45https://doi.org/10.1145/290941.290954Online:01 August 1998Publication History 462citation4,318DownloadsMetricsTotal Citations462Total Downloads4,318Last 12 Months146Last 6 weeks18 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
Distributional Clustering of Words for Text Classification
Authors: L. Douglas Baker, Andrew Kachites McCallum
Venue: SIGIR
Year: 1998

This paper describes the application of Distributional Clustering [20] to document classification. This approach clusters words into groups based on the distribution of class labels associated with each word. Thus, unlike some other unsupervised dimensionalityreduction techniques, such as Latent Semantic Indexing, we are able to compress the feature space much more aggressively, while still maintaining high document classification accuracy. Experimental results obtained on three real-world data sets show that we can reduce the feature dimensionality by three orders of magnitude and lose only 2% accuracy---significantly better than Latent Semantic Indexing [6], class-based clustering [1], feature selection by mutual information [23], or Markov-blanket-based feature selection [13]. We also show that less aggressive clustering sometimes results in improved classification accuracy over classification without clustering. 1 Introduction The popularity of the Internet has caused an exponent...
Resolving Ambiguity for Cross-Language Retrieval
Authors: Lisa Ballesteros, W. Bruce Croft
Venue: SIGIR
Year: 1998

One of the main hurdles to improved CLIR effectiveness is resolving ambiguity associated with translation. Availability of resources is also a problem. First we present a technique based on co-occurrence statistics from unlinked corpora which can be used to reduce the ambiguity associated with phrasal and term translation.
Measures of Relative Relevance and Ranked Half-Life: Performance Indicators for Interactive IR
Authors: Pia Borlund, Peter Ingwersen
Venue: SIGIR
Year: 1998

This paper introduces the concepts of the relative relevance (RR) measure and a new performance indicator of the positional strength of the retrieved and ranked documents. The former is seen as a measure of associative performance computed by the application of the Jaccard formula. The latter is named the Ranked Half-Life (RHL) indicator and denotes the degree to which relevant documents are located on the top of a ranked retrieval result. The measures are proposed to be applied in addition to the traditional performance parameters such as precision and/or recall in connection with evaluation of interactive IR systems. The RR measure describes the degree of agreement between the types of relevance applied in evaluation of information retrieval (IR) systems in a non-binary assessment context. It is shown that the measure has potential to bridge the gap between subjective and objective relevance, as it makes it possible to understand and interpret the relation between these two main classes of relevance used in interactive IR experiments. The relevance concepts are defined, and the application of the measures is demonstrated by interrelating three types of relevance assessments: algorithmic; intellectual topical@ and; situational assessments. Further, the paper shows that for a given set of queries at given precision levels the RHL indicator adds to the understanding of comparisons of IR performance.
Learning While Filtering Focuments
Authors: James P. Callan
Venue: SIGIR
Year: 1998

This paper examines the problems of learning queries and dissemination thresholds from relevance feedback in a dynamic information filtering environment. It revisits the EG algorithm for learning queries, identifying several problems in using it reliably for information filtering, and providing solutions. It also presents a new algorithm for learning dissemination thresholds automatically, from the same relevance feedback information used to learn queries.
Cross-Language Information Retrieval with the UMLS Metathesaurus
Authors: David Eichmann, Miguel E. Ruiz, Padmini Srinivasan
Venue: SIGIR
Year: 1998

We investigate an automatic method for Cross Language Information Retrieval (CLIR) that utilizes the multilingual UMLS Metathesaurus to translate Spanish and French natural language queries into English. Two experiments are presented using OHSUMED, a subset of MEDLINE. Both experiments examine retrieval effectiveness of the translated queries. However, in the second experiment, the query translation procedure is augmented with digram based vocabulary normalization procedures. In this comparative study of retrieval effectiveness the measures used are: 11--point--average precision score (11--AvgP); average interpolated precision at recall of 0.1; and noninterpolated (i.e., exact) precision after 10 retrieved documents. Our results indicate that for Spanish the UMLS Metathesaurus based CLIR method appears equivalent to multilingual dictionary based approaches investigated in the current literature. French yields less favorable results and our analysis suggests that linguistic differences ...
A Theory of Term Weighting Based on Exploratory Data Analysis
Authors: Warren R. Greiff
Venue: SIGIR
Year: 1998

Techniques of exploratory data analysis are used to study the weight of evidence that the occurrence of a query term provides in support of the hypothesis that a document is relevant to an information need. In particular, the relationship between the document frequency and the weight of evidence is investigated.
Experiments in Japanese Text Retrieval and Routing Using the NEAT System
Authors: Gareth J. F. Jones, Tetsuya Sakai, Masahiro Kajiura, Kazuo Sumita
Venue: SIGIR
Year: 1998

This paper describes a structured investigation into the retrieval of Japanese text. The study includes a comparison of different indexing strategies for documents and queries, investigation of term weighting strategies principally derived for use with English texts, and the application of relevance feedback for query expansion. Results on the standard BMIR-Jl and BMIR-J2 Japanese retrieval collections indicate that term weighting transfers well to Japanese text. Indexing using dictionary based morphological analysis and character strings are both shown to be individually effective, but marginally better in combination.
Spatial Querying for Image Retrieval: A User-Oriented Evaluation
Authors: Joemon M. Jose, Jonathan Furner, David J. Harper
Venue: SIGIR
Year: 1998

Epic is an image retrieval system that implements a novel spatial-querying mechanism. A usercentred, task-oriented, comparative evaluation of Epic was undertaken in which two versions of the system--one set up to enable spatial queries only, the other allowing textual queries only-were compared. Use was made of the two systems by design professionals in simulated work task situations, and quantitative and qualitative data collected as indicators of the levels of users' satisfaction. Re sults demonstrated that users often had a 'mental image' of a potentially satisfying picture in mind, that they were happy to express this need in visual terms, and that in doing so they preferred to have access to Epic's spatialquerying facility. Success in obtaining statistically significant results appears to support validation of the novel methodological framework adopted. 1
The Impact of Query Structure and Query Expansion on Retrieval Performance
Authors: Jaana Kekäläinen, Kalervo Järvelin
Venue: SIGIR
Year: 1998

The effects of query structures and query expansion (QE) on retrieval performance were tested with a best match retrieval system (INQUERY'). Query structure means the use of operators to express the relations between search keys. Eight different structures were tested, representing weak structures (averages and weighted averages of the weights of the keys) and strong structures (e.g., queries with more elaborated search key relations). QE was based on concepts, which were first selected from a conceptual model, and then expanded by semantic relationships given in the model. The expansion levels were (a) no expansion, (b) a synonym expansion, (c) a narrower concept expansion, (d) an associative concept expansion, and (e) a cumulative expansion of all other expansions.