The starting point of this paper is the observation that methods based on the direct
match of keywords are inadequate because they do not consider the cognitive ability
of concept formation and abstraction. We argue that keyword evaluation needs to
be based on a semantic model of language capturing the semantic relatedness of
words to satisfy the claim of the human-like ability of concept formation and abstraction
and achieve better evaluation results. Evaluation of keywords is difficult since semantic
informedness is required for this purpose. This model must be capable of identifying
semantic relationships such as synonymy, hypernymy, hyponymy, and location-based
abstraction. For example, when gathering texts from online sources, one usually finds
a few keywords with each text. Still, these keyword sets are neither complete for the
text nor are they in themselves closed, i.e., in most cases, the keywords are a random
subset of all possible keywords and not that informative w.r.t. the complete keyword set.
Therefore all algorithms based on this cannot achieve good evaluation results and provide
good/better keywords or even a complete keyword set for a text. As a solution, we
propose a word graph that captures all these semantic relationships for a given language.
The problem with the hyponym/hyperonym relationship is that, unlike synonyms, it is not
bidirectional. Thus the space of keyword sets requires a metric that is non-symmetric, in
other words, a quasi-metric. We sketch such a metric that works on our graph. Since it
is nearly impossible to obtain such a complete word graph for a language, we propose
for the keyword task a simpler graph based on the base text upon which the keyword
sets should be evaluated. This reduction is usually sufficient for evaluating keyword sets.
| Identifer | oai:union.ndltd.org:DRESDEN/oai:qucosa:de:qucosa:85869 |
| Date | 08 June 2023 |
| Creators | Kölbl, Max, Kyogoku, Yuki, Philipp, J. Nathanael, Richter, Michael, Rietdorf, Clements, Yousef, Tariq |
| Publisher | Frontiers Media S.A. |
| Source Sets | Hochschulschriftenserver (HSSS) der SLUB Dresden |
| Language | English |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, doc-type:article, info:eu-repo/semantics/article, doc-type:Text |
| Rights | info:eu-repo/semantics/openAccess |
| Relation | 801564 |
Page generated in 0.0023 seconds