Open AccessPERSONAL NAME ALIASES ON AUTOMATIC DISCOVERY FROM THE WEB
Author(s) -
Y. Sarath Kumar,
Eswar Kodali,
P. Harini
Publication year - 2015
Publication title -
international journal of computer and communication technology
Language(s) - English
Resource type - Journals
eISSN - 2231-0371
pISSN - 0975-7449
DOI - 10.47893/ijcct.2015.1296
Subject(s) - alias , computer science , information retrieval , mean reciprocal rank , set (abstract data type) , rank (graph theory) , identification (biology) , natural language processing , data mining , mathematics , botany , combinatorics , biology , programming language
In this paper we proposed a lexical-pattern-based approach to extract aliases of a given name. We use a set of names and their aliases as training data to extract lexical patterns that describe numerous ways in which information related to aliases of a name is presented on the web. An individual is typically referred by numerous name aliases on the web. Accurate identification of aliases of a given person name is useful in various web related tasks such as information retrieval, sentiment analysis, personal name disambiguation, and relation extraction. We propose a method to extract aliases of a given personal name from the web. Given a personal name, the proposed method first extracts a set of candidate aliases. Second, we rank the extracted candidates according to the likelihood of a candidate being a correct alias of the given name. We evaluate the proposed method on three data sets: an English personal names data set, an English place names data set, and a Japanese personal names data set. The proposed method outperforms numerous baselines and previously proposed name alias extraction methods, achieving a statistically significant mean reciprocal rank (MRR) of 0.67.