UA-ZSA: Web Page Clustering on the basis of Name Disambiguation

Proceedings of the 4th International Workshop on Semantic Evaluations (SemEval-2007), pages 338–341, Prague, June 2007. c⃝2007 Association for Computational Linguistics UA-ZSA: Web Page Clustering on the basis of Name Disambiguation Zornitsa Kozareva, Sonia Vazquez, Andres Montoyo DLSI, University of Alicante Carretera de San Vicente S/N Alicante, Spain 03080 zkozareva,svazquez,montoyo@dlsi.ua.es Abstract This paper presents an approach for web page clustering. The different underlying meanings of a name are discovered on the basis of the title of the web page, the body content, the common named entities across the documents and the sub-links. This in- formation is feeded into a K-Means cluster- ing algorithm which groups together the web pages that refer to the same individual. 1 Introduction Ambiguity is the task of building up multiple alter- native linguistic structures for a single input. Most of the approaches focus on word sense disambigua- tion (WSD), where the sense of a word has to be determined depending on the context in which it is used. The same problem arises for named entities shared by different people or for grandsons named after their grandparents. For instance, querying the name “Michael Hammond” in the World Wide Web where there are huge quantities of massive and un- structured data, a search engine retrieves thousands of documents related to this name. However, there are several individuals sharing the name “Michael Hammon”. One is a biology professor at the Univer- sity of Arizona, another is at the University of War- wick, there is a mathematician from Toronto among others. The question is which one of these refer- ents we are actually looking for and interested in. Presently, to be able to answer to this question, we have to skim the content of the documents and re- trieve the correct answers on our own. To automate this process, the named entities can be disambiguated and the different underlying meanings of the name can be found. On the basis of this information, the web pages can be clustered together and organized in a hierarchical structure which can ease the documents’ browsing. This is also the objective of the Web People Search (WePS) task (Artiles et al., 2007). What makes the WePS task even more challenging is the fact that in con- trast to WSD where the number of senses of a word are predefined, in WePS we do not know the exact number of different individuals. For the resolution of the WePS task, we have de- veloped a web page clustering approach using the title and the body content of the web pages. In ad- dition, we group together the documents that share many location, person and organization names, as well as those that point out to the same sub-links. The rest of the paper is organized as follows. In Section 2 we describe various approaches for name disambiguation and discrimination. Our approach is shown in Section 3, the obtained results and a dis- cussion are provided in Section 4 and finally we con- clude in Section 5. 2 Related …

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