Search (9 results, page 1 of 1)

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Abstract

A lattice-based model for information retrieval was suggested in the 1960's but has been seen as a theoretical possibility hard to practically apply ever since. This paper attempts to revive the lattice model and demonstrate its applicability in an information retrieval system, FalR, that incorporates a graphical representation of a faceted thesaurus. It shows how Boolean queries can be lattice-theoretically related to the concepts of the thesaurus and visualized within the thesaurus display. An advantage of FaIR is that it allows for a high level of transparency of the system, which can be controlled by the user

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Abstract

This paper discusses how facet-like structures occur as a commonplace feature in a variety of computer science disciplines as a means for structuring class hierarchies. The paper then focuses on a mathematical model for facets (and class hierarchies in general), called formal concept analysis, and discusses graphical representations of faceted systems based on this model.

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Abstract

Controlled vocabulary and fixed citation order are two of the mechanisms used to effect collocation in traditional bibliographic classification schemes. Analysis of the rationale underlying application of each of these mechanisms provides a framework for the development of nontraditional approaches to the organization of resources available an the World Wide Web. When supported by an extralinguistic faceted vocabulary of concepts, this framework facilitates construction and implementation of flexible, dynamic indexing systems that can be applied in the design of electronic information systems and the organization of Web-based knowledge resources.

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Abstract

This paper describes a graphical interface for the navigation and construction of faceted thesauri that is based on formal concept analysis. Each facet of a thesaurus is represented as a mathematical lattice that is further subdivided into components. Users can graphically navigate through the Java implementation of the interface by clicking on terms that connect facets and components. Since there are many applications for thesauri in the knowledge representation field, such a graphical interface has the potential of being very useful

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Date

22. 1.2016 17:47:06

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Date

22. 1.2016 17:30:31

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Date

22. 1.2016 17:30:31

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Abstract

The writers show that a faceted navigation structure makes web sites easier to use. They begin by analyzing the web sites of three library and information science faculties, and seeing if the sites easily provide the answers to five specific questions, e.g., how the school ranks in national evaluations. (It is worth noting that the web site of the Faculty of Information Studies and the University of Toronto, where this bibliography is being written, would fail on four of the five questions.) Using examples from LIS web site content, they show how facets can be related and constructed, and use concept diagrams for illustration. They briefly discuss constraints necessary when joining facets: for example, enrolled students can be full- or part-time, but prospective and alumni students cannot. It should not be possible to construct terms such as "part-time alumni" (see Yannis Tzitzikas et al, below in Background). They conclude that a faceted approach is best for web site navigation, because it can clearly show where the user is in the site, what the related pages are, and how to get to them. There is a short discussion of user interfaces, and the diagrams in the paper will be of interest to anyone making a facet-based web site. This paper is clearly written, informative, and thought-provoking. Uta Priss's web site lists her other publications, many of which are related and some of which are online: http://www.upriss.org.uk/top/research.html.

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Abstract

This paper argues that the Semantic Web needs to incorporate both formal and associative structures (and possibly a multitude of other structures and strategies) to be successful. The arguments for this claim are based on an observation of successes and failures in the areas of artificial intelligence (AI) and natural language processing (NLP). 1. Introduction The WWW provides numerous challenges for information and knowledge processing activities. Information may be available but not accessible or retrievable because of language barriers or insufficient search strategies. Data mining techniques may discover implicit information in explicit data but these techniques do not necessarily guarantee that the discovered information is relevant, significant and trustworthy. During the last several decades hundreds or thousands of computer and information scientists have developed probably thousands of natural language processing and artificial intelligence techniques that were aimed at solving problems related to intelligent information processing only to encounter more and more new obstacles along the way. The latest solution, the Semantic Web, appears as an open declaration of defeat: since natural language processing and AI techniques did not provide sufficient results, it is now proposed to put the burden an the shoulder of the authors of webpages who are expected to populate their pages with metadata and additional markup. Metadata is essentially a new form of controlled vocabulary; markup - at least in the form of XML, XSL, etc - is essentially a programming language. Existing studies of the use of controlled vocabularies and indexing practices in information science and studies of teaching programming languages to "everybody" (Python, 2002) have shown that both are difficult and full of unsolved problems. This can further dampen the expectations of the success of the Semantic Web. In contrast to machines and despite numerous inter-cultural conflicts around the world, humans do communicate surprisingly successfully even across national, linguistic and cultural boundaries. The question then arises: why are humans successful at information processing tasks such as information integration, translation and communication, which computers find so difficult? One obvious answer is that human cognition is embodied and grounded in our shared experiences of living in the same world. AI researchers have theoretically explored the idea of symbol grounding in the early 1990's but so far, connectionist artificial agents with perceptual interfaces have not been integrated with a large-scale capability of symbolic representations.