On the Web, there are limited ways of finding people sharing similar interests or background with a given person. The current methods, such as using regular search engines, are either ineffective or time consuming. In this work, a new approach for searching people sharing similar interests from the Web, called People-Search, is presented. Given a person, to find similar people from the Web, there are two major research issues: person representation and matching persons. In this study, a person representation method which uses a person's website to represent this person's interest and background is proposed. The design of matching process takes person representation into consideration to allow the same representation to be used when composing the query, which is also a personal website. Based on this person representation method, the main proposed algorithm integrates textual content and hyperlink information of all the pages belonging to a personal website to represent a person and match persons. Other algorithms, based on different combinations of content, inlink, and outlink information of an entire personal website or only the main page, are also explored and compared to the main proposed algorithm. Two kinds of evaluations were conducted. In the automatic evaluation, precision, recall, F and Kruskal-Goodman Gamma measures were used to compare these algorithms. In the human evaluation, the effectiveness of the main proposed algorithm and two other important ones were evaluated by human subjects. Results from both evaluations show that the People-Search algorithm integrating content and link information of all pages belonging to a personal website outperformed all other algorithms in finding similar people from the Web.
展开▼
