Search (24 results, page 2 of 2)

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Abstract

The human's expressing general concepts in uncontrolled natural language, his information need, and meaning recognition in and essence selection from texts are indeterminate processes and therefore defy any satisfactory formalization and programming. Where the equivalence or even superiority of algorithmic approaches to these golas has been claimed, the authors have worked under artificial, experimental conditions and/or have in their evaluation referred to those approaches that are far from exploiting the capabilities of intellectual content analysis, representation and query phrasing

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Abstract

The tight adherence to dogmas, created and advocated by authorities and disseminated through hearsay, constitutes an impediment to the progress badly needed in view of the low effectiveness of the vast majority of our bibliographic information systems. The Italian mathematician and physicist Galileo has become famous not only for his discoveries but also for his being exposed to the rejective and even hostile attitude on the part of his contemporaries when he contradicted several dogmas prevailing at that time. This obstructive attitude can be traced throughout the centuries and manifests itself in the field of modern information science, too. An example is the allegedly necessary, inevitable precision/recall relationship, as most recently postulated again by Lancaster (1994). It is believed to be confirmed by emprical evidence, with other empirical evidence to the contrary being neglected. This case even constitutes an example of the suppression of truth in the interest of upholding a dogma

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Abstract

Natural text phrasing is an indeterminate process and, thus, inherently lacks representational predictability. This holds true in particular in the Gase of general concepts and of their syntactical connectivity. Hence, natural language query phrasing and searching is an unending adventure of trial and error and, in most Gases, has an unsatisfactory outcome with respect to the recall and precision ratlos of the responses. Human indexing is based an knowledgeable document interpretation and aims - among other things - at introducing predictability into the representation of documents. Due to the indeterminacy of natural language text phrasing and image construction, any adequate indexing is also indeterminate in nature and therefore inherently defies any satisfactory algorithmization. But human indexing suffers from a different Set of deficiencies which are absent in the processing of non-interpreted natural language. An optimally effective information System combines both types of language in such a manner that their specific strengths are preserved and their weaknesses are avoided. lf the goal is a large and enduring information system for more than merely known-item searches, the expenditure for an advanced index language and its knowledgeable and careful employment is unavoidable.

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Abstract

Traditionally, database indexing and book indexing have been looked upon as being quite distinct and have been kept apart in textbooks and teaching. The traditional borderline between both variations of indexing, however, should not conceal fundamental commonalities of the two approaches. For example, theausurus construction and usage, quite common in databases, has hardly been encountered in book indexing so far. Database indexing, on the other hand, has hardly made use of subheadings of the syntax-displaying type, quite common in book indexing. Most database users also prefer precombining vocabulary units and reject concept analysis. However, insisting on precombining descriptors in a large database vocabulary may, in the long run, well be destructive to the quality, of indexing and of the searches. A complementary approach is conceivable which provides both precombinations and analyzed subjects, both index language syntax and subheadings, and provides access to an information system via precombinations, without jeopardizing the manageability of the vocabulary. Such an approach causes considerable costs in input because it involves a great deal of intellectual work. On the other hand, much time and costs will be saved in the use of the system. In addition, such an approach would endow an information system with survival power