PMING Distance: A Collaborative Semantic Proximity Measure
- 1 December 2012
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2, 442-449
- https://doi.org/10.1109/wi-iat.2012.226
Abstract
One of the main problems that emerges in the classic approach to semantics is the difficulty in acquisition and maintenance of ontologies and semantic annotations. On the other hand, the flow of data and documents which are accessible from the Web is continuously fueled by the contribution of millions of users who interact digitally in a collaborative way. Search engines, continually exploring the Web, are therefore the natural source of information on which to base a modern approach to semantic annotation. A promising idea is that it is possible to generalize the semantic similarity, under the assumption that semantically similar terms behave similarly, and define collaborative proximity measures based on the indexing information returned by search engines. In this work PMING, a new collaborative proximity measure based on search engines, which uses the information provided by search engines, is introduced as a basis to extract semantic content. PMING is defined on the basis of the best features of other state-of-the-art proximity distances which have been considered. It defines the degree of relatedness between terms, by using only the number of documents returned as result for a query, then the measure dynamically reflects the collaborative change made on the web resources. Experiments held on popular collaborative and generalist engines (e.g. Flickr, Youtube, Google, Bing, Yahoo Search) show that PMING outperforms state-of-the-art proximity measures (e.g. Normalized Google Distance, Flickr Distance etc.), in modeling contexts, modeling human perception, and clustering of semantic associations.Keywords
This publication has 12 references indexed in Scilit:
- Graph Spectra and the Detectability of Community Structure in NetworksPhysical Review Letters, 2012
- Measuring semantic similarity between words by removing noise and redundancy in web snippetsConcurrency and Computation: Practice and Experience, 2011
- A Web Search Engine-Based Approach to Measure Semantic Similarity between WordsIEEE Transactions on Knowledge and Data Engineering, 2010
- Flickr distancePublished by Association for Computing Machinery (ACM) ,2008
- PLANNING IN REACTIVE ENVIRONMENTSComputational Intelligence, 2007
- Graph-based word clustering using a web search enginePublished by Association for Computational Linguistics (ACL) ,2006
- Generalized vector spaces model in information retrievalPublished by Association for Computing Machinery (ACM) ,1985
- Repetition priming and frequency attenuation in lexical access.Journal of Experimental Psychology: Learning, Memory, and Cognition, 1984
- Basic objects in natural categoriesCognitive Psychology, 1976
- Interaction of information in word recognition.Psychological Review, 1969