There are various kinds of valuable semantic information about real-world entities embedded in web pages and databases. Extracting and integrating these entity information from the Web is of great significance. Comparing to traditional information extraction problems, web entity extraction needs to solve several new challenges to fully take advantage of the unique characteristic of the Web. In this paper, we introduce our recent work on statistical extraction of structured entities, named entities, entity facts and relations from Web. We also briefly introduce iKnoweb, an interactive knowledge mining framework for entity information integration. We will use two novel web applications, Microsoft Academic Search (aka Libra) and EntityCube, as working examples.
AHAMED, SHAIK MUNEEB; AHMAD, SD.AFZAL; and BABU, P.
"ENTITY EXTRACTION USING STATISTICAL METHODS USING INTERACTIVE KNOWLEDGE MINING FRAMEWORK,"
International Journal of Communication Networks and Security: Vol. 2
, Article 14.
Available at: https://www.interscience.in/ijcns/vol2/iss1/14