Collaborative reputation mechanisms for online communities

Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 1999.Includes bibliographical references (p. 79-80).The members of electronic communities are often unrelated to each other, they may have never met and have no information on each other's reputation. This kind of information is vital in Electronic Commerce interactions, where the potential counterpart's reputation can be a significant factor in the negotiation strategy. I will investigate two complementary reputation mechanisms that rely on collaborative rating and personalized evaluation of the various ratings assigned to each user. While these reputation mechanisms are developed in the context of electronic commerce, I believe that they may have applicability in other types of electronic communities such as chatrooms, newsgroups, mailing lists etc.by Giorgos Zacharia.S.M

Regularized algorithms for ranking, and manifold learning for related tasks

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2009.Includes bibliographical references (leaves 119-127).This thesis describes an investigation of regularized algorithms for ranking problems for user preferences and information retrieval problems. We utilize regularized manifold algorithms to appropriately incorporate data from related tasks. This investigation was inspired by personalization challenges in both user preference and information retrieval ranking problems. We formulate the ranking problem of related tasks as a special case of semi-supervised learning. We examine how to incorporate instances from related tasks, with the appropriate penalty in the loss function to optimize performance on the hold out sets. We present a regularized manifold approach that allows us to learn a distance metric for the different instances directly from the data. This approach allows incorporation of information from related task examples, without prior estimation of cross-task coefficient covariances. We also present applications of ranking problems in two text analysis problems: a) Supervise content-word learning, and b) Company Entity matching for record linkage problems.by Giorgos Zacharia.Ph.D

PERSONALIZED RECOMMENDATIONS BY LEARNING FROM RELATED DATA

In this paper we investigate how to incorporate preference ranking data available from related individuals to improve individual specific preference learning models. We present regularized learning methods for learning ranking functions from choice based comparisons of the form “the individual prefers a candidate feature combination over all other presented choices”. In other ranking or supervised information retrieval problems, the training data includes explicit or implicit relevance rankings, either by experts, or by empirical observations. In the choice based conjoint problem we only know what the winning combination is. We transform the problem to a binary classification task of pairwise comparisons, and use a regularized loss function to account for noise in the users ’ choices. Then we investigate how to better learn personalized ranking functions by combining information from individual and aggregate data. Recent work in multitask learning has shown that data from related tasks can be used effectively by regularized nonlinear loss functions that penalize errors based on aggregate data less than the errors from the individual data. We extend these approaches with a graph Laplacian transformation, to show how to pose the same problem as a special case of semi-supervised learning, a solution with regularized manifolds, and supporting experiments

Trust management through reputation mechanisms

This paper proposes reputation mechanisms that rely on collaborative ratings and personalized evaluation of the various ratings assigned to each user. Reputation is usually defined as the amount of trust inspired by a particular perso

Design Methodology of an Online Greek Language Course

We present a participatory design methodology for developing an online community supported Modern Greek language course. The students of the classes collaborate in transcribing real audio lessons, publish and peer review shared notes. Participatory design was implemented as

Website content accessibility of 30,000 cypriot web sites

This paper extends previous studies [10, 12, 13] that investigated the accessibility of different web sites of specific content and context to an analysis of the whole web of a specific country (Cyprus). To our knowledge no previous study has analyzed such a big number of web sites for accessibility in a single study. More specifically this paper evaluates the compliance of 30,000 Cyprus related websites spidered by Arachne (http://search.kypros.org ) search engine. The 30,000 Cyprus related websites where evaluated for accessibility using the Bobby (http://www.cast.org/bobby/) accessibility tool. Statistical analysis and comparison of the accessibility ratings for the different main domain categories (commercial, academic, governmental, and organizational) of the Cypriot web are also provided