2,486 research outputs found
Word sense disambiguation and information retrieval
It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval
(IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will
increase. However, recent research into the application of a word sense disambiguator to an IR system failed
to show any performance increase. From these results it has become clear that more basic research is needed
to investigate the relationship between sense ambiguity, disambiguation, and IR.
Using a technique that introduces additional sense ambiguity into a collection, this paper presents research
that goes beyond previous work in this field to reveal the influence that ambiguity and disambiguation have
on a probabilistic IR system. We conclude that word sense ambiguity is only problematic to an IR system
when it is retrieving from very short queries. In addition we argue that if a word sense disambiguator is to
be of any use to an IR system, the disambiguator must be able to resolve word senses to a high degree of
accuracy
Word sense disambiguation and information retrieval
It has often been thought that word sense ambiguity is a cause of poor performance in Information Retrieval
(IR) systems. The belief is that if ambiguous words can be correctly disambiguated, IR performance will
increase. However, recent research into the application of a word sense disambiguator to an IR system failed
to show any performance increase. From these results it has become clear that more basic research is needed
to investigate the relationship between sense ambiguity, disambiguation, and IR.
Using a technique that introduces additional sense ambiguity into a collection, this paper presents research
that goes beyond previous work in this field to reveal the influence that ambiguity and disambiguation have
on a probabilistic IR system. We conclude that word sense ambiguity is only problematic to an IR system
when it is retrieving from very short queries. In addition we argue that if a word sense disambiguator is to
be of any use to an IR system, the disambiguator must be able to resolve word senses to a high degree of
accuracy
Formal models, usability and related work in IR (editorial for special edition)
The Glasgow IR group has carried out both theoretical and empirical work, aimed at giving end users efficient and effective access to large collections of multimedia data
NASARI: a novel approach to a Semantically-Aware Representation of items
The semantic representation of individual word senses and concepts is of fundamental importance to several applications in Natural Language Processing. To date, concept modeling techniques have in the main based their representation either on lexicographic resources, such as WordNet, or on encyclopedic resources, such as Wikipedia. We propose a vector representation technique that combines the complementary knowledge of both these types of resource. Thanks to its use of explicit semantics combined with a novel cluster-based dimensionality reduction and an effective weighting scheme, our representation attains state-of-the-art performance on multiple datasets in two standard benchmarks: word similarity and sense clustering. We are releasing our vector representations at http://lcl.uniroma1.it/nasari/
Analysis of equivalence mapping for terminology services
This paper assesses the range of equivalence or mapping types required to facilitate interoperability in the context of a distributed terminology server. A detailed set of mapping types were examined, with a view to determining their validity for characterizing relationships between mappings from selected terminologies (AAT, LCSH, MeSH, and UNESCO) to the Dewey Decimal Classification (DDC) scheme. It was hypothesized that the detailed set of 19 match types proposed by Chaplan in 1995 is unnecessary in this context and that they could be reduced to a less detailed conceptually-based set. Results from an extensive mapping exercise support the main hypothesis and a generic suite of match types are proposed, although doubt remains over the current adequacy of the developing Simple Knowledge Organization System (SKOS) Core Mapping Vocabulary Specification (MVS) for inter-terminology mapping
From Word to Sense Embeddings: A Survey on Vector Representations of Meaning
Over the past years, distributed semantic representations have proved to be
effective and flexible keepers of prior knowledge to be integrated into
downstream applications. This survey focuses on the representation of meaning.
We start from the theoretical background behind word vector space models and
highlight one of their major limitations: the meaning conflation deficiency,
which arises from representing a word with all its possible meanings as a
single vector. Then, we explain how this deficiency can be addressed through a
transition from the word level to the more fine-grained level of word senses
(in its broader acceptation) as a method for modelling unambiguous lexical
meaning. We present a comprehensive overview of the wide range of techniques in
the two main branches of sense representation, i.e., unsupervised and
knowledge-based. Finally, this survey covers the main evaluation procedures and
applications for this type of representation, and provides an analysis of four
of its important aspects: interpretability, sense granularity, adaptability to
different domains and compositionality.Comment: 46 pages, 8 figures. Published in Journal of Artificial Intelligence
Researc
An effective, low-cost measure of semantic relatedness obtained from Wikipedia links
This paper describes a new technique for obtaining measures of semantic relatedness. Like other recent approaches, it uses Wikipedia to provide structured world knowledge about the terms of interest. Out approach is unique in that it does so using the hyperlink structure of Wikipedia rather than its category hierarchy or textual content. Evaluation with manually defined measures of semantic relatedness reveals this to be an effective compromise between the ease of computation of the former approach and the accuracy of the latter
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