OpenRaiser/Intern-Atlas huggingface dataset:
On the Evaluation of Boolean Operators in the Extended Boolean Retrieval Framework
Authors: Joon Ho Lee, Won Yong Kim, Myoung-Ho Kim, Yoon-Joon Lee
Venue: SIGIR
Year: 1993

The retrieval models based on the extended boolean retrieval framework, e.g., the fuzzy set model and the extended boolean model have been proposed in the past to provide the conventional boolean retrieval system with the document ranking facility. However, due to undesirable properties of evaluation formulas for the AND and OR operations, the former generates incorrect ranked output in certain cases and the latter suffers from the complexity of computation. There have been a variety of fuzzy operators to replace the evaluation formulas. In this paper we first investigate the behavioral aspects of the fuzzy operators and address important issues to affect retrieval effectiveness. We then define an operator class called positively compensatory operators giving high retrieval effectiveness, and present a pair of positively compensatory operators providing high retrieval efficiency as well as high retrieval effectiveness. All the claims are justified through experiments.
Compression of Indexes with Full Positional Information in Very Large Text Databases
Authors: Gordon Linoff, Craig Stanfill
Venue: SIGIR
Year: 1993

This paper describes a combination of compression methods which may be used to reduce the size of inverted indexes for very large text databases. These methods are Prefix Omission, Run-Length Encoding, and a novel family of numeric representations called n-s coding. Using these compression methods on two different text sources (the King James Version of the Bible and a sample of Wall Street Journal Stories), the compressed index occupies less than 40% of the size of the original text, even when both stopwords and numbers are included in the index. The decreased time required for I/O can almost fully compensate for the time needed to uncompress the postings. This research is part of an effort to handle very large text databases on the CM-5, a massively parallel MIMD supercomputer.
Simple Word Strings as Compound Keywords: An Indexing and Ranking Method for Japanese Texts
Authors: Yasushi Ogawa, Ayako Bessho, Masako Hirose
Venue: SIGIR
Year: 1993

This paper describes a new indexing method for Japanese text databases using the simple keyword string, in which a compound word is treated as a string of simple words, which are the smallest units in Japanese grammar which still maintain their meanings. This method allows retrieved texts to be ranked, according to the similarity of their meaning to the query, without using a control vocabulary or thesaurus. This paper also introduces the keyword feature, which describes the syntactic and semantic characteristics of a word, and results in more precise keyword extraction and text retrieval as well as simple dictionary maintenance.
The Identification of Important Concepts in Highly Structured Technical Papers
Authors: Chris D. Paice, Paul A. Jones
Venue: SIGIR
Year: 1993

Automatic abstracting, typically based on extraction of important sentences from a text, has been treated as a largely separate task from automatic indexing. This paper describes an approach in which the indexing and abstracting tasks are effectively combined. It is applicable to highly structured empirical research papers, whose content can be organised using a semantic frame. During a scan of a source text, stylistic clues and constructs are used for extracting candidate fillers for the various slots in the frame. Subsequently, an actual concept name is chosen for each slot by comparing the various candidates and their weights.
A Browser for Bibliographic Information Retrieval, Based on an Application of Lattice Theory
Authors: Gert Schmeltz Pedersen
Venue: SIGIR
Year: 1993

An application of mathematical lattice theory, called relationship lattices, is utilized to attack problems of operational bibliographic information retrieval.The proposed solution offers an interface to the information searcher enabling operation in a world of concepts, authors, and document records and their relationships. This hides the complexities of query language and database structures, and it allows to use a personally preferred terminology and to browse, query and download document records in a convenient way.The main component of the proposed solution is a personal thesaurus built up as a relationship lattice.
Concept Based Query Expansion
Authors: Yonggang Qiu, Hans-Peter Frei
Venue: SIGIR
Year: 1993

Query expansion methods have been studied for a long time - with debatable success in many instances. In this paper we present a probabilistic query expansion model based on a similarity thesaurus which was constructed automatically. A similarity thesaurus reflects domain knowledge about the particular collection from which it is constructed. We address the two important issues with query expansion: the selection and the weighting of additional search terms. In contrast to earlier methods, our queries are expanded by adding those terms that are most similar to the concept of the query, rather than selecting terms that are similar to the query terms. Our experiments show that this kind of query expansion results in a notable improvement in the retrieval effectiveness when measured using both recall-precision and usefulness.
Content Awareness in a File System Interface: Implementing the 'Pile' Metaphor for Organizing Information
Authors: Daniel E. Rose, Richard Mander, Tim Oren, Dulce B. Ponceleon, Gitta Salomon, Yin Yin Wong
Venue: SIGIR
Year: 1993

The pile is a new element of the desktop user interface metaphor, designed to support the casual organization of documents. An interface design based on the pile concept suggested uses of content awareness for describing, organizing, and filing textual documents. We describe a prototype implementation of these capabilities, and give a detailed example of how they might appear to the user. We believe the system demonstrates how content awareness can be not only used in a computer filing system, but made an integral part of the user's experience.
SPIDER: A Multiuser Information Retrieval System for Semistructured and Dynamic Data
Authors: Peter Schäuble
Venue: SIGIR
Year: 1993

The access structure, the retrieval model, and the system architecture of the SPIDER information retrieval system are described. The access structure provides efficient weighted retrieval on dynamic data collections. It is based on signatures and non-inverted item descriptions. The signatures provide upper bounds for the exact retrieval status values such that only a small number of exact retrieval status values have to be computed. SPIDER's retrieval model is a probabilistic retrieval model that is capable to exploit the database scheme of semistructured data collections. This model can be considred as a further development of the Binary Independence Indexing (BII) model. The system architecture was derived systematically from a given set of requirements such as effective and efficient retrieval on dynamic data collections, exploitation of the database scheme, computed views, and the integration of information retrieval functionality and database functionality.
Computation of Term Associations by a Neural Network
Authors: S. K. Michael Wong, Y. J. Cai, Yiyu Yao
Venue: SIGIR
Year: 1993

This paper suggests a method for computing term associations based on an adaptive bilinear retrieval model. Such a model can be implemented by using a three-layer feedforward neural network. Term associations are modeled by weighted links connecting different neurons, and are derived by the perception learning algorithm without the need for introducing any ad hoc parameters. The preliminary results indicate the usefulness of neural networks in the design of adaptive information retrieval systems.
An Application of Least Squares Fit Mapping to Text Information Retrieval
Authors: Yiming Yang 0002, Christopher G. Chute
Venue: SIGIR
Year: 1993

This paper describes a unique example-based mapping method for document retrieval. We discovered that the knowledge about relevance among queries and documents can be used to obtain empirical connections between query terms and the canonical concepts which are used for indexing the content of documents. These connections do not depend on whether there are shared terms among the queries and documents; therefore, they are especially effective for a mapping from queries to the documents where the concepts are relevant but the terms used by article authors happen to be different from the terms of database users. We employ a Linear Least Squares Fit (LLSF) technique to compute such connections from a collection of queries and documents where the relevance is assigned by humans, and then use these connections in the retrieval of documents where the relevance is unknown. We tested this method on both retrieval and indexing with a set of MEDLINE documents which has been used by other information retrieval systems for evaluations. The effectiveness of the LLSF mapping and the significant improvement over alternative approaches was evident in the tests.
Relevance Feedback With Too Much Data
Authors: James Allan
Venue: SIGIR
Year: 1995

Modern text collections often contain large documents that span several subject areas. Such documents are problematic for relevance feedback since inappropriate terms can easily be chosen. This study explores the highly effective approach of feeding back passages of large documents. A less-expensive method that discards long documents is also reviewed and found to be effective if there are enough relevant documents. A hybrid approach that feeds back short documents and passages of long documents may be the best compromise. 1 Introduction As the amount of on-line text has increased, so has the size of individual documents in those collections. Information retrieval methods that could easily be applied to the full text of abstracts or short documents are sometimes less effective or prohibitively expensive for large documents. This problem has led to a resurgence of interest in techniques for handling large texts, including passage retrieval, theme identification, document summarization...
Detecting Content-Bearing Words by Serial Clustering
Authors: Abraham Bookstein, Shmuel T. Klein, Timo Raita
Venue: SIGIR
Year: 1995

Article Free AccessDetecting content-bearing words by serial clustering—extended abstract Share on Authors: A. Bookstein Center for Information and Language Studies, University of Chicago, Chicago, IL Center for Information and Language Studies, University of Chicago, Chicago, ILView Profile , S. T. Klein Dept. of Math. & CS, Bar Ilan University, Ramat-Gan 52900, Israel Dept. of Math. & CS, Bar Ilan University, Ramat-Gan 52900, IsraelView Profile , T. Raita Comp. Sci. Dept., University of Turku, 20520 Turku, Finland Comp. Sci. Dept., University of Turku, 20520 Turku, FinlandView Profile Authors Info & Claims SIGIR '95: Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrievalJuly 1995 Pages 319–327https://doi.org/10.1145/215206.215377Online:01 July 1995Publication History 3citation425DownloadsMetricsTotal Citations3Total Downloads425Last 12 Months5Last 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
Netserf: Using Semantic Knowledge to Find Internet Information Archives
Authors: Anil S. Chakravarthy, Kenneth B. Haase
Venue: SIGIR
Year: 1995

This paper describes the architecture, implementation and evaluation of NetSerf, a program for finding information archives on the Internet using natural language queries. NetSerf's query processor extracts structured, disambiguated representations from the queries. The query representations are matched to hand-coded representations of the archives using semantic knowledge from WordNet (a semantic thesaurus) and an on-line Webster's dictionary. NetSerf has been tested using a set of questions and answers developed independently for a game called Internet Hunt. The paper presents results comparing the performance of NetSerf and the standard IRs ystem SMART on this set of queries.
Fast and Quasi-Natural Language Search for Gigabits of Chinese Texts
Authors: Lee-Feng Chien
Venue: SIGIR
Year: 1995

Article Fast and quasi-natural language search for gigabytes of Chinese texts Share on Author: Lee-Feng Chien Institute of Information Science, Academia Sinica, Taipei, Taiwan, R.O.C. Institute of Information Science, Academia Sinica, Taipei, Taiwan, R.O.C.View Profile Authors Info & Claims SIGIR '95: Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrievalJuly 1995 Pages 112–120https://doi.org/10.1145/215206.215345Online:01 July 1995Publication History 26citation508DownloadsMetricsTotal Citations26Total Downloads508Last 12 Months6Last 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
One Term Or Two?
Authors: Kenneth Ward Church
Venue: SIGIR
Year: 1995

How effective is stemming? Text normalization? Stemming experiments test two hypotheses: one term (+stemmer) or two (–stemmer). The truth lies somewhere in between. The correlations, ρ, between a word and its variants (e.g., + s, + ly, +uppercase) tend to be small (refuting the one term hypothesis), but non-negligible (refuting the two term hypothesis). Moreover, ρ varies systematically depending on the words involved; it is relatively large for a good keyword, ρ(hostage , hostages) ∼∼0. 5, and small for pairs with little content, ρ(anytime, Anytime) ∼∼0, or conflicting content, ρ(continental , Continental) ∼∼0.
Probability Kinematics in Information Retrieval
Authors: Fabio Crestani, C. J. van Rijsbergen
Venue: SIGIR
Year: 1995

We analyse the kinematics of probabilistic term weights at retrieval time for di erent Information Retrieval models. We present four models based on di erent notions of probabilistic retrieval. Two of these models are based on classical probability theory and can be considered as prototypes of models long in use in Information Retrieval, like the Vector Space Model and the Probabilistic Model. The two other models are based on a logical technique of evaluating the probability of a conditional called imaging, one is a generalisation of the other. We analyse the transfer of probabilities occurring in the term space at retrieval time for these four models, compare their retrieval performance using classical test collections, and discuss the results. We believe that our results provide useful suggestions on how to improve existing probabilistic models of Information Retrieval by taking into consideration term-term similarity.
A Case-Based Approach To Intelligent Information Retrieval
Authors: Jody J. Daniels, Edwina L. Rissland
Venue: SIGIR
Year: 1995

We have built a hybrid Case-Based Reasoning (CBR) and Information Retrieval (IR) system that generates a query to the IR system by using information derived from CBR analysis of a problem situation. The query is automatically formed by submitting in text form a set of highly relevant cases, based on a CBR analysis, to a modified version of INQUERY&apos;s relevance feedback module. This approach extends the reach of CBR, for retrieval purposes, to much larger corpora and injects knowledge-based techniques into traditional IR. 1 Introduction One strength of Case-Based Reasoning (CBR) systems is the ability to reason about a problem case and perform highly intelligent problem-solving, such as the generation of legal arguments or detailed operational plans [9]. In particular, CBR systems have at their core the ability to retrieve highly relevant cases. However, CBR systems are limited by the availability of cases actually represented in their case bases. Among current case-based reasoning syst...
Integrating IR and RDBMS Using Cooperative Indexing
Authors: Samuel DeFazio, Amjad M. Daoud, Lisa Ann Smith, Jagannathan Srinivasan, W. Bruce Croft, James P. Callan
Venue: SIGIR
Year: 1995

The full integration of information retrieval (IR) features into a database management system (DBMS) has long been recognized as both a significant goal and a challenging undertaking. By full integration we mean: i) support for document storage, indexing, retrieval, and update, ii) transaction semantics, thus all database operations on documents have the ACID properties of atomicity, consistency, isolation, and durability, iii) concurrent addition, update, and retrieval of documents, and iv) database query language extensions to provide ranking for document retrieval operations. It is also necessary for the integrated offering to exhibit scaleable performance for document indexing and retrieval processes, To identify the implementation requirements imposed by the desired level of integration, we layered a representative IR application on Oracle Rdb and then conducted a number of database load and document retrieval experiments. The results of these experiments suggest that infrastructural extensions are necessary to obtain both the desired level of IR integration and scaleable performance. With the insight gained from our initial experiments, we developed an approach, called cooperative indexing, that provides a framework to achieve both scalability and full integration of IR and RDBMS technology. Prototype implementations of system-level extensions to support cooperative indexing were evaluated with a modified version of Oracle Rdb. Our experimental findings validate the cooperative indexing scheme and suggest alternatives to further improve performance.
Parallel Text Retrieval on a High Performance Super Computer Using the Vector Space Model
Authors: Pavlos S. Efraimidis, Christos Glymidakis, Basilis Mamalis, Paul G. Spirakis, Basil Tampakas
Venue: SIGIR
Year: 1995

This paperl discusses the efi-iciency of a parallel text retrieval system that is based on the Vector Space Model. Specifically, we describe a general parallel retrieval algorithm for use with this model, the application of the algorithm in the FIRE system [I], and its implementation on the high performance GCe131512 Parsytec parallel machine [2]. The use of this machine's t we-dimensional grid of processors provides an efficient baais for the virtual tree that lies at the heart of our retrieval algorithm. Analytical and experimental evidence is presented to demonstrate the efficiency of the algorithm. the Vector Space Model, which makes the parallel algorithm quite simple. In the following two sections the FIRE system and the GCe13/512 machine (the two basic tools of our work) are briefly presented. In section 4, we demonstrate a simple algorithm that can be used for parallelizing almost any information retrieval system based on the Vector Space Model. This algorithm is partially used in the design and im-
Partial Orders for Document Representation: A New Methodology for Combining Document Features
Authors: Steven Finch
Venue: SIGIR
Year: 1995

This paper describes a novel paradigm for representing many types of information about documents in a manner particularly suited to text categorization by a trivial empirical rule induction system. It also has potential application to full-text retrieval paradigms. The paradigm allows many different types of document predicates to be combined together with logical dependencies being controlled for. This is shown to be justified by any reasonable model of descriptor inference, and the effect of increasing representation sophistication is shown for two corpora. 1
Information Processing in the Context of Medical Care
Authors: Valerie Florance, Gary Marchionini
Venue: SIGIR
Year: 1995

Article Free Access Share on Information processing in the context of medical care Authors: Valerie Florance Division of Medical Informatics, University of Rochester Medical Center, Rochester, NY Division of Medical Informatics, University of Rochester Medical Center, Rochester, NYView Profile , Gary Marchionini College of Library and Information Services, University of Maryland, College Park, MD College of Library and Information Services, University of Maryland, College Park, MDView Profile Authors Info & Claims SIGIR '95: Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrievalJuly 1995 Pages 158–163https://doi.org/10.1145/215206.215353Published:01 July 1995Publication History 13citation525DownloadsMetricsTotal Citations13Total Downloads525Last 12 Months19Last 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
Towards New Measures of Information Retrieval Evaluation
Authors: William R. Hersh, Diane L. Elliot, David H. Hickam, Stephanie L. Wolf, Anna Molnar, Christine Leichtenstien
Venue: SIGIR
Year: 1995

All of the methods currently used to assess information retrieval (IR) systems have limitations in their ability to measure how well users are able to acquire information. We utilized a new approach to assessing information obtained, based on a short-answer test given to senior medical students. Students took the ten-question test and then searched one of two IR systems on the five questions for which they were least certain of their answer Our results showed that pre-searching scores on the test were low but that searching yielded a high proportion of answers with both systems. These methods are able to measure information obtained, and will be used in subsequent studies to assess differences among IR systems.
Searchers and Searchers: Differences between the Most and Least Consistent Searchers
Authors: Mirja Iivonen
Venue: SIGIR
Year: 1995

Article Free Access Share on Searchers and searchers: differences between the most and least consistent searches Author: Mirja Iivonen Department of Information Studies, University of Tampere, P.O. Box 607, FIN-33101 Tampere, Finland Department of Information Studies, University of Tampere, P.O. Box 607, FIN-33101 Tampere, FinlandView Profile Authors Info & Claims SIGIR '95: Proceedings of the 18th annual international ACM SIGIR conference on Research and development in information retrievalJuly 1995 Pages 149–157https://doi.org/10.1145/215206.215352Published:01 July 1995Publication History 10citation433DownloadsMetricsTotal Citations10Total Downloads433Last 12 Months8Last 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 SiteeReaderPDF