Search (66 results, page 2 of 4)

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Abstract

Brajnik et alia describe their view of an effective retrieval interface, one which coaches the searcher using stored knowledge not only of database structure, but of strategic situations which are likely to occur, such as repeating failed tactics in a low return search, or failing to try relevance feedback techniques. The emphasis is on the system suggesting search strategy improvements by relating them to an analysis of work entered so far and selecting and ranking those found relevant. FIRE is an interface utilizing these techniques. It allows the user to assign documents to useful, topical and trash folders, maintains thesauri files automatically searchable on query terms, and it builds, using user entries and a rule system, a picture of the retrieval situation from which it generates suggestions. Six participants used FIRE in INSPEC20K database searches, two for their own information needs and four needs provided by the authors. Satisfaction was measured in a structured post search interview, behavior by log analysis, and performance by recall and precision in the canned searches. Participants found the suggestions helpful, but insisted they would have taken those approaches without such assistance. Users took the suggestions offered and preferred those demanding the least effort.

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Abstract

The study adopts a naturalistic approach to investigate users' interaction with a browsable MeSH (medical subject headings) display designed to facilitate query construction for the PubMed bibliographic database. The purpose of the study is twofold: first, to test the usefulness of a browsable interface utilizing the principle of faceted classification; and second, to investigate users' preferred query submission methods in different problematic situations. An interface that incorporated multiple query submission methods - the conventional single-line query box as well as methods associated the faceted classification display was constructed. Participants' interactions with the interface were monitored remotely over a period of 10 weeks; information about their problematic situations and information retrieval behaviors were also collected during this time. The traditional controlled experiment was not adequate in answering the author's research questions; hence, the author provides his rationale for a naturalistic approach. The study's findings show that there is indeed a selective compatibility between query submission methods provided by the MeSH display and users' problematic situations. The query submission methods associated with the display were found to be the preferred search tools when users' information needs were vague and the search topics unfamiliar. The findings support the theoretical proposition that users engaging in an information retrieval process with a variety of problematic situations need different approaches. The author argues that rather than treat the information retrieval system as a general purpose tool, more attention should be given to the interaction between the functionality of the tool and the characteristics of users' problematic situations.

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Date

15.12.2000 20:22:37

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Date

22. 7.2006 18:17:44

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Date

22. 7.2006 18:35:39

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Abstract

Die Schaffung eines natürlichsprachlichen Interfaces (NLI), (das einem Nutzer die Formulierung von Anfragen an Informationsanbieter in seiner Muttersprache erlaubt, stellt eine der interessantesten Herausforderungen im Bereich des Information-Retrieval und der Verarbeitung natürlicher Sprache dar. Dieser Beitrag beschreibt Methoden zur Obersetzung natürlichsprachlicher Anfragen in Ausdrücke formaler Retrievalsprachen sowohl für Informationsressourcen im Internet als auch für lokale Datenbanken. Die vorgestellten Methoden sind Teil das Informationsrecherchesystems LINAS, das an der Fernuniversität Hagen entwickelt wurde, um Nutzern einen natürlichsprachlichen Zugang zu lokalen und zu im Internet verteilten wissenschaftlichen und technischen Informationen anzubieten. Das LINAS-System unterscheidet sich von anderen Systemen und natürlichsprachlichen Interfaces (vgl. OSIRIS) oder die früheren Systeme INTELLECT, Q&A durch die explizite Einbeziehung von Hintergrundwissen und speziellen Dialogmodellen in den Übersetzungsprozeß. Darüber hinaus ist das System auf ein vollständiges Verstehen des natürlichsprachlichen Textes ausgerichtet, während andere Systeme typischerweise nur nach Stichworten oder bestimmten grammatikalischen Mustern in der Eingabe suchen. Ein besonderer Schwerpunkt von LINAS liegt in der Repräsentation und Auswertung der semantischen Relationen zwischen den in der Nutzeranfrage gegebenen Konzepten

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Source

Library hi tech. 22(2004) no.2, S.182-197

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Date

22. 7.2006 18:37:49

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Date

22. 7.2006 17:58:06

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Date

22. 7.2006 18:01:11

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Date

22. 7.2006 18:23:19

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Date

22. 7.2006 18:30:09

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Abstract

Computers have become our companions in many of the activities we pursue in our life. They assist us, in particular, in searching relevant information that is needed to perform a variety of tasks, from professional usage to personal entertainment. They hold this information in a huge number of heterogeneous sources, either dedicated to a specific user community (e.g., enterprise databases) or maintained for the general public (e.g., websites and digital libraries). Whereas progress in basic information technology is nowadays capable of guaranteeing effective information management, information retrieval and dissemination has become a core issue that needs further accomplishments to achieve user satisfaction. The research communities in databases, information retrieval, information visualization, and human-computer interaction have already largely investigated these domains. However, the technical environment has so dramatically evolved in recent years, inducing a parallel and very significant evolution in user habits and expectations, that new approaches are definitely needed to meet current demand. One of the most evident and significant changes is the human-computer interaction paradigm. Traditional interactions relayed an programming to express user information requirements in formal code and an textual output to convey to users the information extracted by the system. Except for professional data-intensive application frameworks, still in the hands of computer speciahsts, we have basically moved away from this pattern both in terms of expressing information requests and conveying results. The new goal is direct interaction with the final user (the person who is looking for information and is not necessarily familiar with computer technology). The key motto to achieve this is "go visual." The well-known high bandwidth of the human-vision channel allows both recognition and understanding of large quantities of information in no more than a few seconds. Thus, for instance, if the result of an information request can be organized as a visual display, or a sequence of visual displays, the information throughput is immensely superior to the one that can be achieved using textual support. User interaction becomes an iterative query-answer game that very rapidly leads to the desired final result. Conversely, the system can provide efficient visual support for easy query formulation. Displaying a visual representation of the information space, for instance, lets users directly point at the information they are looking for, without any need to be trained into the complex syntax of current query languages. Alternatively, users can navigate in the information space, following visible paths that will lead them to the targeted items. Again, thanks to the visual support, users are able to easily understand how to formulate queries and they are likely to achieve the task more rapidly and less prone to errors than with traditional textual interaction modes.
The two facets of "going visual" are usually referred to as visual query systems, for query formulation, and information visualization, for result display. Visual Query Systems (VQSs) are defined as systems for querying databases that use a visual representation to depict the domain of interest and express related requests. VQSs provide both a language to express the queries in a visual format and a variety of functionalities to facilitate user-system interaction. As such, they are oriented toward a wide spectrum of users, especially novices who have limited computer expertise and generally ignore the inner structure of the accessed database. Information visualization, an increasingly important subdiscipline within the field of Human-Computer Interaction (HCI), focuses an visual mechanisms designed to communicate clearly to the user the structure of information and improve an the cost of accessing large data repositories. In printed form, information visualization has included the display of numerical data (e.g., bar charts, plot charts, pie charts), combinatorial relations (e.g., drawings of graphs), and geographic data (e.g., encoded maps). In addition to these "static" displays, computer-based systems, such as the Information Visualizer and Dynamic Queries, have coupled powerful visualization techniques (e.g., 3D, animation) with near real-time interactivity (i.e., the ability of the system to respond quickly to the user's direct manipulation commands). Information visualization is tightly combined with querying capabilities in some recent database-centered approaches. More opportunities for information visualization in a database environment may be found today in data mining and data warehousing applications, which typically access large data repositories. The enormous quantity of information sources an the World-Wide Web (WWW) available to users with diverse capabilities also calls for visualization techniques. In this article, we survey the main features and main proposals for visual query systems and touch upon the visualization of results mainly discussing traditional visualization forms. A discussion of modern database visualization techniques may be found elsewhere. Many related articles by Daniel Keim are available at http://www. informatik.uni-halle.de/dbs/publications.html.

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22. 7.2006 17:38:51

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22. 3.2008 14:35:21

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22. 3.2008 14:29:25

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22. 7.2006 18:19:20

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22. 3.2008 14:24:08

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Abstract

A natural language interface to an expert system is a program that enables the user to communicate with the system in English or some other human language. It is designed to spare the user from learning some special programming language or command input language. Today this input is almost always typed at a keyboard or assembled with a mouse. Only a few research systems understand spoken input and produce spoken output. The precise definition of an expert system is a matter of argument. For the purposes of this article an expert system is a computer system that is capable of providing expert advice or otherwise performing at an expert level, usually in a rather narrow area. An excellent discussion of the controversy surrounding this term is given in Ref. 1. A typical expert system has at least three different kinds of interfaces. Some have four. One interface is designed to understand user queries and commands, another to generate answers and explanations. The knowledge-engineering interface provides a way for a human expert to endow the system with the expertise it needs to function. This may be a natural language interface as well. Some expert systems also produce documents, such as medical case reports or legal wills or petitions for divorce. The first paradigm expert system, Shortliffe's MYCIN system (2), provided natural language interfaces for both the end user and the engineer. The first widely used expert system that Shortliffe developed, ONCOCIN (3, 4), not only provided natural language interfaces for the end user and the knowledge engineer, it also generated the lengthy patient reports required by complex drug trials. In this article we will concentrate mainly an the natural language understanding and generation required to communicate with the end user, but we will also discuss interfaces for the knowledge engineer. We will describe some document generation techniques briefly.
The explanation facility, the ability to display its reasoning to the user, has been a key component of the expert system from the very beginning. Even though this facility may not be used very often, its presence gives users some crucial reassurance that they can explore the system's decision-making processes and themselves make a reasoned decision about whether or not to accept the advice given by the system. Elaine Rich (S) was the first to enunciate a fundamental principle of explanation generation in expert systems: It is essential that the explanation generated be derived from the actual decision-making process used by the system so that as that process changes, the explanations change with it. If the system relies an previously stored "canned explanations," then changes in the rules or the inference processes will leave the system providing explanations that are no longer valid. She argues also that the system can give deeper explanations if it operates off the internal reasoning process. From the very beginning, expert systems were thought of as vehicles for learning, particularly through the text that the system provides to explain its reasoning. When William Clancey (6) set out to produce a tutoring system based an the MYCIN system, people thought that this was going to be a quick and easy thesis, but Clancey soon realized that MYCIN's rules, written by experts for other practicing physicians, were not an appropriate way to teach diagnosis to medical students. He spent 10 years building and rebuilding the NEOMYCIN/GUIDON system as an effective tutoring system for medical students. Because of the historic connection between expert sytems and tutoring systems, we add a discussion of natural language interfaces for tutoring systems at the end of this article. Dialogue issues are becoming important as hardware systems speed up and software systems become sophisticated enough to carry an an actual dialogue with the user. This is particularly true in tutoring systems that teach languages. We will conclude with a brief mention of some systems of the future that are still in the research stage.

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