Search (63 results, page 2 of 4)

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Abstract

The second half of a 'before and after' study to evaluate the impact of an online catalogue on subject searching behaviour is reported. A holistic approach is adopted encompassing both catalogue use and browsing at the shelves for catalogue users and non-users. Verbal and non-verbal data were elicited from searchers using a combined methodology including talk-aloud technique, observation and a screen logging facility. An extensive qualitative analysis was carried out correlating expressed topics, search formulation strategies and documents retrieved at the shelves. The online catalogue environment does not appear to have increased the extent of subject searching nor the use of the bibliographic tool. The manual PRECIS index supported a contextual approach for broad and more interactive search formulations whereas the OPAC encouraged a matching approach and narrow formulations with fewer but user generated formulations. The success rate of the online catalogue was slightly better than that of the manual tools but fewer items were retrieved at the shelves. Non-users of the bibliographic tools seemed to be just as successful. To improve retrieval effectiveness it is suggested that online catalogues should cater for both matching and contextual approaches to searching. Recent research indicates that a more interactive process could be promoted by providing query expansion through a combination of searching aids for matching, for search formulation assistance and for structured contextual retrieval

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Abstract

Context plays an important role in a number of domains where reasoning intervenes as in understanding, interpretation, diagnosis, etc. The reason is that reasoning activities heavily rely on a background (or experience) that is generally not made explicit and that gives a contextual dimension to knowledge. On the Web in December 1996, AItaVista gave more than 710000 pages containing the word context, when concept gives only 639000 references. A clear definition of this word stays to be found. There are several formal definitions of this concept (references are given in Brézillon, 1996): a set of preferences and/or beliefs, an infinite and only partially known collection of assumptions, a list of attributes, the product of an interpretation, possible worlds, assumptions under which a statement is true or false. One faces the same situation at the programming level: a collection of context schemas; a path in information retrieval; slots in object-oriented languages; a special, buffer-like data structure; a window on the screen, buttons which are functional customisable and shareable; an interpreter which controls the system's activity; the characteristics of the situation and the goals of the knowledge use; or entities (things or events) related in a certain way that permits to listen what is said and what is not said. Context is often assimilated at a set of restrictions (e.g., preconditions) that limit access to parts of the applications. The first works considering context explicitly are in Natural Language. Researchers in this domain focus on the linguistic context, sometimes associated with other types of contexts as: semantic context, cognitive context, physical and perceptual context, and social context (Bunt, 1997).

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Abstract

In this article, we report research on an algorithmic approach to alleviating search uncertainty in a large information space. Grounded on object filtering, automatic indexing, and co-occurence analysis, we performed a large-scale experiment using a parallel supercomputer (SGI Power Challenge) to analyze 400.000+ abstracts in an INSPEC computer engineering collection. Two system-generated thesauri, one based on a combined object filtering and automatic indexing method, and the other based on automatic indexing only, were compaed with the human-generated INSPEC subject thesaurus. Our user evaluation revealed that the system-generated thesauri were better than the INSPEC thesaurus in 'concept recall', but in 'concept precision' the 3 thesauri were comparable. Our analysis also revealed that the terms suggested by the 3 thesauri were complementary and could be used to significantly increase 'variety' in search terms the thereby reduce search uncertainty

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Abstract

The goal of this study is to evaluate, compare, and contrast how facet analysis is used to construct the systematic or faceted displays of a selection of information retrieval thesauri. More specifically, the study seeks to examine which principles of facet analysis are used in the thesauri, and the extent to which different thesauri apply these principles in the same way. A measuring instrument was designed for the purpose of evaluating the structure of faceted thesauri. This instrument was applied to fourteen faceted information retrieval thesauri. The study reveals that the thesauri do not share a common definition of what constitutes a facet. In some cases, the thesauri apply both enumerative-style classification and facet analysis to arrange their indexing terms. A number of the facets used in the thesauri are not homogeneous or mutually exclusive. The principle of synthesis is used in only 50% of the thesauri, and no one citation order is used consistently by the thesauri.

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Abstract

Latent Semantic Analysis (LSA) is a theory and method for extracting and representing the contextual-usage meaning of words by statistical computations applied to a large corpus of text (Landauer and Dumais, 1997). The underlying idea is that the aggregate of all the word contexts in which a given word does and does not appear provides a set of mutual constraints that largely determines the similarity of meaning of words and sets of words to each other. The adequacy of LSA's reflection of human knowledge has been established in a variety of ways. For example, its scores overlap those of humans on standard vocabulary and subject matter tests; it mimics human word sorting and category judgments; it simulates word-word and passage-word lexical priming data; and as reported in 3 following articles in this issue, it accurately estimates passage coherence, learnability of passages by individual students, and the quality and quantity of knowledge contained in an essay.

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Abstract

Knowledge and Inference discusses an important problem for software systems: How do we treat knowledge and ideas on a computer and how do we use inference to solve problems on a computer? The book talks about the problems of knowledge and inference for the purpose of merging artificial intelligence and library science. The book begins by clarifying the concept of ""knowledge"" from many points of view, followed by a chapter on the current state of library science and the place of artificial intelligence in library science. Subsequent chapters cover central topics in the artificial intelligence: search and problem solving, methods of making proofs, and the use of knowledge in looking for a proof. There is also a discussion of how to use the knowledge system. The final chapter describes a popular expert system. It describes tools for building expert systems using an example based on Expert Systems-A Practical Introduction by P. Sell (Macmillian, 1985). This type of software is called an ""expert system shell."" This book was written as a textbook for undergraduate students covering only the basics but explaining as much detail as possible.

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Abstract

The Electronic Libraries and Information Highways MITRE Sponsored Research project aims to help searchers working in digital libraries increase their chance of matching the language of authors. Focuses on whether query formulation can be improved through the addition of semantic knowledge that is interactively gathered from a thesaurus that exists in a distributed, interoperating, cooperative environment. A prototype, ELVIS, was built that improves information retrieval through query expansion and is based on publicly available Z39.50 standard thesauri integrated with networked information discovery and retrieval tools

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Abstract

Explores interface design raised by the development and evaluation of Okapi, a highly interactive information retrieval system based on a probabilistic retrieval model with relevance feedback. It uses terms frequency weighting functions to display retrieved items in a best match ranked order; it can also find additional items similar to those marked as relevant by the searcher. Compares the effectiveness of automatic and interactive query expansion in different user interface environments. focuses on the nature of interaction in information retrieval and the interrelationship between functional visibility, the user's cognitive loading and the balance of control between user and system

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Abstract

In the field of electronic publishing, encyclopedias represent a unique sort of text for investigating advanced methods of navigation. The user of an electronic excyclopedia normally expects special methods for accessing the entries in an encyclopedia database. Navigation through printed encyclopedias in the traditional sense focuses on the alphabetic order of the entries. In electronic encyclopedias, however, thematic structuring of lemmas and, of course, extensive (hyper-) linking mechanisms have been added. This paper will focus on showing developments, which go beyond these navigational strucutres. We will concentrate on the semantic space formed by lemmas to build a network of semantic distances and thematic trails through the encyclopedia

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Abstract

Focuses on the user and human-computer interaction (HCI) aspects of the research based on the Okapi text retrieval system. Describes 3 experiments using different approaches to query expansion, highlighting the relationship between the functionality of a system and different interface designs. These experiments involve both automatic and interactive query expansion, and both character based and GUI (graphical user interface) environments. The effectiveness of the search interaction for query expansion depends on resolving opposing interface and functional aspects, e.g. automatic vs. interactive query expansion, explicit vs. implicit use of a thesaurus, and document vs. query space

Footnote

Contribution to a thematic issue on Okapi and information retrieval research

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Content

Enthält die Abschnitte: What constitutes a record; What constitutes a word and what 'words' to index; Use of stop lists; Use of suffixing or stemming; Advanced automatic indexing techniques (term weighting, query expansion, the use of multiple-word phrases for indexing)

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Abstract

Describes a deductive data model based on 3 abstraction levels for representing vocabularies for information retrieval: conceptual level; expression level; and occurrence level. The proposed data model can be used for the representation and navigation of indexing and retrieval thesauri and as a vocabulary source for concept based query expansion in heterogeneous retrieval environments

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Abstract

Reports an evaluation of 3 methods for the expansion of natural language queries in ranked output retrieval systems. The methods are based on term co-occurrence data, on Soundex codes, and on a string similarity measure. Searches for 110 queries in a data base of 26.280 titles and abstracts suggest that there is no significant difference in retrieval effectiveness between any of these methods and unexpanded searches

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Abstract

Provides an introduction to the use of n-grams in textual information systems, where an n-gram is a string of n, usually adjacent, characters, extracted from a section of continuous text. Applications that can be implemented efficiently and effectively using sets of n-grams include spelling errors detection and correction, query expansion, information retrieval with serial, inverted and signature files, dictionary look up, text compression, and language identification

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Abstract

The ENQUIRE project forms part of a series of investigations on query expansion in the Okapi experimental text retrieval system. A configurable user interface was implemented as an evaluative tool and tested in two locations on two different databases: the library catalogue of The London Business SChool and the computing section of INSPEC. The system offered a range of possible strategies based on thesaural terms for reformulating queries. These could be initiated automatically by the system or interactively with the user. The formative phase of the evaluation established the appropriateness and usability of the interface as well as users' perceptions of the underlying functionality. The aim of the large scale field trial was to determine to what extent user would select thesaural terms suggested by the system to reformulate queries, and to evaluate the effectiveness of a new dynamic form of query expansion implemented for this project

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Abstract

Presents a neural network approach to document semantic indexing. Reports results of a study to apply a Hopfield net algorithm to simulate human associative memory for concept exploration in the domain of computer science and engineering. The INSPEC database, consisting of 320.000 abstracts from leading periodical articles was used as the document test bed. Benchmark tests conformed that 3 parameters: maximum number of activated nodes; maximum allowable error; and maximum number of iterations; were useful in positively influencing network convergence behaviour without negatively impacting central processing unit performance. Another series of benchmark tests was performed to determine the effectiveness of various filtering techniques in reducing the negative impact of noisy input terms. Preliminary user tests conformed expectations that the Hopfield net is potentially useful as an associative memory technique to improve document recall and precision by solving discrepancies between indexer vocabularies and end user vocabularies

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Abstract

Currently, most approaches to retrieving textual materials from scientific databases depend on a lexical match between words in users' requests and those in or assigned to documents in a database. Because of the tremendous diversity in the words people use to describe the same document, lexical methods are necessarily incomplete and imprecise. Using the singular value decomposition (SVD), one can take advantage of the implicit higher-order structure in the association of terms with documents by determining the SVD of large sparse term by document matrices. Terms and documents represented by 200-300 of the largest singular vectors are then matched against user queries. We call this retrieval method Latent Semantic Indexing (LSI) because the subspace represents important associative relationships between terms and documents that are not evident in individual documents. LSI is a completely automatic yet intelligent indexing method, widely applicable, and a promising way to improve users...

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Abstract

The explosive growth of the Internet and other sources of networked information have made automatic mediation of access to networked information sources an increasingly important problem. Much of this information is expressed as electronic text, and it is becoming practical to automatically convert some printed documents and recorded speech to electronic text as well. Thus, automated systems capable of detecting useful documents are finding widespread application. With even a small number of languages it can be inconvenient to issue the same query repeatedly in every language, so users who are able to read more than one language will likely prefer a multilingual text retrieval system over a collection of monolingual systems. And since reading ability in a language does not always imply fluent writing ability in that language, such users will likely find cross-language text retrieval particularly useful for languages in which they are less confident of their ability to express their information needs effectively. The use of such systems can be also be beneficial if the user is able to read only a single language. For example, when only a small portion of the document collection will ever be examined by the user, performing retrieval before translation can be significantly more economical than performing translation before retrieval. So when the application is sufficiently important to justify the time and effort required for translation, those costs can be minimized if an effective cross-language text retrieval system is available. Even when translation is not available, there are circumstances in which cross-language text retrieval could be useful to a monolingual user. For example, a researcher might find a paper published in an unfamiliar language useful if that paper contains references to works by the same author that are in the researcher's native language.
Multilingual text retrieval can be defined as selection of useful documents from collections that may contain several languages (English, French, Chinese, etc.). This formulation allows for the possibility that individual documents might contain more than one language, a common occurrence in some applications. Both cross-language and within-language retrieval are included in this formulation, but it is the cross-language aspect of the problem which distinguishes multilingual text retrieval from its well studied monolingual counterpart. At the SIGIR 96 workshop on "Cross-Linguistic Information Retrieval" the participants discussed the proliferation of terminology being used to describe the field and settled on "Cross-Language" as the best single description of the salient aspect of the problem. "Multilingual" was felt to be too broad, since that term has also been used to describe systems able to perform within-language retrieval in more than one language but that lack any cross-language capability. "Cross-lingual" and "cross-linguistic" were felt to be equally good descriptions of the field, but "crosslanguage" was selected as the preferred term in the interest of standardization. Unfortunately, at about the same time the U.S. Defense Advanced Research Projects Agency (DARPA) introduced "translingual" as their preferred term, so we are still some distance from reaching consensus on this matter.
I will not attempt to draw a sharp distinction between retrieval and filtering in this survey. Although my own work on adaptive cross-language text filtering has led me to make this distinction fairly carefully in other presentations (c.f., (Oard 1997b)), such an proach does little to help understand the fundamental techniques which have been applied or the results that have been obtained in this case. Since it is still common to view filtering (detection of useful documents in dynamic document streams) as a kind of retrieval, will simply adopt that perspective here.

Type

a

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Abstract

Examines how, for term based free text retrieval, Interactive Query Expansion (IQE) provides better retrieval performance tahn Automatic Query Expansion (AQE) but the performance of IQE depends on the strategy employed by the user to select expansion terms. The aim is to build an expert query expansion system using term selection rules based on expert users' strategies. It is expected that such a system will achieve better performance for novice or inexperienced users that either AQE or IQE. The procedure is to discover expert IQE users' term selection strategies through observation and interrogation, to construct a rule based query expansion (RQE) system based on these and to compare the resulting retrieval performance with that of comparable AQE and IQE systems

Type

a