Notice of Violation of IEEE Publication Principles - A semantic distance measure for matching web services

2009 ◽  
Author(s):  
Huirong Yang ◽  
Shanshan Liu ◽  
Pengbin Fu ◽  
Haihuan Qin ◽  
Liheng Gu
Keyword(s):  
Web Services ◽  
Distance Measure ◽  
Semantic Distance

AN ALGEBRAIC APPROACH TO INDUCTIVE LEARNING

2001 ◽  
Vol 10 (01n02) ◽  
pp. 257-272
Author(s):  
ZDRAVKO MARKOV
Keyword(s):  
Concept Learning ◽  
Lattice Theory ◽  
Distance Measure ◽  
Inductive Learning ◽  
Algebraic Approach ◽  
Semantic Distance ◽  
Conceptual Clustering ◽  
Horn Clauses ◽  
Concept Hierarchies ◽  
Attribute Value

The paper presents a framework to induction of concept hierarchies based on consistent integration of metric and similarity-based approaches. The hierarchies used are subsumption lattices induced by the least general generalization operator (lgg) commonly used in inductive learning. Using some basic results from lattice theory the paper introduces a semantic distance measure between objects in concept hierarchies and discusses its applications for solving concept learning and conceptual clustering tasks. Experiments with well known ML datasets represented in three types of languages - propositional (attribute-value), atomic formulae and Horn clauses, are also presented.

Semantic web services matchmaking: Semantic distance-based approach

2013 ◽  
Vol 39 (2) ◽  
pp. 497-511 ◽  
Author(s):  
Tamer A. Farrag ◽  
Ahmed I. Saleh ◽  
H.A. Ali
Keyword(s):  
Web Services ◽  
Semantic Web ◽  
Semantic Distance ◽  
Semantic Web Services

A personalized search using a semantic distance measure in a graph-based ranking model

2011 ◽  
Vol 37 (6) ◽  
pp. 614-636 ◽  
Author(s):  
Mariam Daoud ◽  
Lynda Tamine ◽  
Mohand Boughanem
Keyword(s):  
Distance Measure ◽  
Similarity Measures ◽  
User Profile ◽  
Semantic Distance ◽  
User Interest ◽  
Document Ranking ◽  
Search Results ◽  
Ranking Models ◽  
Ranking Model ◽  
Extended Graph

The goal of search personalization is to tailor search results to individual users by taking into account their profiles, which include their particular interests and preferences. As these latter are multiple and change over time, personalization becomes effective when the search process takes into account the current user interest. This article presents a search personalization approach that models a semantic user profile and focuses on a personalized document ranking model based on an extended graph-based distance measure. Documents and user profiles are both represented by graphs of concepts issued from predefined web ontology, namely, the Open Directory Project directory (ODP). Personalization is then based on reordering the search results of related queries according to a graph-based document ranking model. This former is based on using a graph-based distance measure combining the minimum common supergraph and the maximum common subgraph between the document and the user profile graphs. We extend this measure in order to take into account a semantic recovery at exact and approximate concept-level matching. Experimental results show the effectiveness of our personalized graph-based ranking model compared with Yahoo and different personalized ranking models performed using classical graph-based measures or vector-space similarity measures.

scholarly journals Metaphor in corpora: a corpus-driven analysis of Applied Linguistics dissertations

2007 ◽  
Vol 7 (1) ◽  
pp. 11-35
Author(s):  
Tony Berber Sardinha
Keyword(s):  
Distance Measure ◽  
Applied Linguistics ◽  
Semantic Distance ◽  
Prior List

This study develops a methodology for finding metaphors in corpora. The procedure is based on the wish that, without a prior list of metaphors, the computer would provide a number of possible metaphor candidates. The methodology works by selecting an initial pool of word types in the corpus, finding shared collocates between pairs of those words and then computing a semantic distance measure for those word pairs which have a requisite number of mutual collocates. Cases which satisfy these criteria were then concordanced and interpreted. This methodology was applied to a corpus of MA dissertations in Applied Linguistics, completed in Brazil. The paper highlights the importance of the use of metaphors by novice Applied Linguistic researchers.

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