The Linguistic dimension in Information Sciences: An applied study to use indexing languages in the work of search engines
The Linguistic dimension in Information Sciences: An applied study to use indexing languages in the work of search engines
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Date
2015-06-13
Authors
Sabri Elhaj, Elmubarak
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Publisher
uofk
Abstract
Thesis Title: the Linguistic dimension in Information
Sciences: An applied study to use indexing languages
in the work of search engines.
Candidates Name: Sabri Elhaj Elmubarak Elamin
Degree: PhD in information & Library Sciences
Graduates college – University of Khartoum
Supervised By: Ustaz. Abu baker Elsiddig Osman
Year: 2007
Along with increasing use of international databases, crosscultural
indexing is becoming more common and tools like
multilingual thesaurus are urgently needed. This study
concentrates on cultural and linguistic problems in
multilingual thesaurus. Very little attention has been paid to
this topic in Arabic research and the need for this kind of
study has grown rapidly. This study has proved that all the
engines tested had ranking schemes that were not well
documented, being based on how many times search words
were mentioned, whether or not they appeared early in the
document, whether or not they appeared close together, and
how many search terms were matched. I did not find the
IV
ranking schemes very useful, as relevant and irrelevant
pages frequently had the same scores. It is found that
aggregating meaning is possible on the Internet because
there are many easily accessible semantic objects to be
harvested. Analysis of the aggregations can suggest patterns
of high likelihood that permit applications to recommend,
adapt, profile, forecast and so on. It has been proved that the
terminology and thesaurus construction standards and
guidebooks provide very little details and consideration
about equivalence. It has been indicated that Google may
index billions of Web pages, but it will never exhaust the
store of meaning of the Web. The reason is that Google's
aggregation strategy is only one of many different strategies
that could be applied to the semantic objects in public Web
space. It has been found that web search engines do not
conspire to suppress controversy, but their strategies do lead
to organizationally dominated search results depriving
searchers of a richer experience and, sometimes, of essential
decision–making information. These experiments suggest
that bias exists, in one form or another, on the Web and
should, in turn, force thinking about content on the Web in a
more controversial light
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