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A Grammar-Based Semantic Similarity Algorithm for …

(2006)A Semantic Similarity Measure for Formal Ontologies. Masters thesis, Alpen-Adria Universität Klagenfurt.

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Merger And Acquisition Thesis - Semantic Similarity Thesis

The evaluation is based on the word disambiguation task developed by Mitchell and Lapata (2008) for intransitive sentences, and on a similar new experiment designed for transitive sentences.

Finally, I apply my similarity metric to the task of assigning words to WORDNET semanticcategories.

There are two main approaches in ontology-based semantic similarity measurement: edge-based (also called structural or hierarchical approach) and node-based (also called information-content approach).

Semantic Similarity Thesis – 516074 – Arbantis

Luckily, a lot of people have dealt with this ‘ontology-based semantic similarity measurement’. I gathered and studied a couple of papers, and provide a quick overview of my findings. See my literature list for a more complete overview.

Edge-based approaches take the structure of the network as a base, focussing on the connections between nodes and their implications/meanings. In edge-based semantic similarity measurement, there are three main principles (which are fortunately pretty much globally agreed-upon – at least in the papers I found):

Miguel Rios (2014) Methods for Measuring Semantic Similarity of Texts

Experimental comparisons to human judgements of semantic similarity for both isolated words as well as words in sentential contexts demonstrate the superiority of this approach over both prototype and exemplar based vector-space models.

The goal is to advance on computational models of meaning and their evaluation. We define two tasks: Semantic Textual Similarity (STS) and Typed Similarity.

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  • A Semantic Similarity Measure for Formal Ontologies - …

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    Semantic Similarity Thesis - We know what makes a truly great writing service

  • WordNet-based semantic similarity measurement - …

    30/10/2011 · WordNet-based semantic similarity measurement ..

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Using semantic similarity measures across Gene Ontology to ..

For ex-ample, they have been used to model judgments of semantic similarity (McDonald, 2000) and association (Denhire and Lemaire, 2004; Griffiths et al., 2007) and have been shown to achieve human level performance on synonymy tests (Landuaer and Dumais, 1997; Griffiths et al., 2007) such as those included in the Test of English as Foreign Language (TOEFL).

Semantic Similarity Calculation of Chinese Word

To evaluate the context-weighted similarity measure I compare ranked similarity lists againstgold-standard resources using precision and recall-based measures from Information Retrieval,since the alternative, application-based evaluation, can often be influenced by distributionalas well as semantic similarity.

Ontology-based semantic web services clustering in …

The Semantic Web aims to provide a more intelligent web by automatically combining information from different, heterogeneous systems. To overcome the barriers posed by this heterogeneity it is necessary to have some kind of automatic integration system. This system not only needs to provide integration services on the syntactic level, but also has to provide integration of the different semantics. This thesis introduces a model for encoding semantics that is based on cognitive principles. Building on this cognitive model a semantic similarity measure is designed that makes it possible to compare the semantics of two or more data sources in order to provide integration services. To show that the approach is usable in real-world situations it is applied to data from the land-use and land-cover domain. Evaluation of this application proves that the cognitive model and semantic similarity measure provide semantically valid results.

Hliaoutakis A (2005) Semantic similarity measures in …

The task of Semantic Textual Similarity (STS) (Agirre et al., 2012) is de- ned as measuring the degree of bidirectional semantic equivalence betweena pair of texts.

Measuring the semantic similarity ..

For example, in Machine Translation evaluation,semantic similarity is used to assess the quality of the machine translationoutput by measuring the degree of equivalence between a referencetranslation and the machine translation output.

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