Tutorial T11-M - Online Trust and Reputation Systems

Neel Sundaresan, eBay Research Labs


The World Wide Web has evolved from the early days of mainly informational plane to the transactional and conversational plane. eCommerce, Social Networks, and other communicative forms like Blogs, Twitter, and P2P messaging systems are prevalant. The challenges that search engines solved were related to page quality and search relevance. HITS, Pagerank and their derivatives solved these problems effectively. In the new web world the challenges include understanding and modelling beyond web pages of people, transactions, communities, and content. This tutorial will discuss trust and reputation systems as they become prime in this new world. We will give an overview of trust and reputation systems as has been studied by social network scientists and computer scientists. We will discuss online implementations of trust and reputation systems. We will discuss interesting research problems in this area and possible applications and platforms as well.


Neel Sundaresan is the head of eBay Research Labs and a Senior Director. He brings to the team and eBay a broad mix of research, technology, and startup experience. His current areas of research interest includes Social and Incentive Networks, Trust and Reputation Systems, Machine Learning as applied to Recommender systems, Classification, Ontology, and Search. He joined eBay in 2005 as a Distinguished Research Scientist. Prior to joining eBay was a founder and CTO of a startup focused on multi-attribute fuzzy search and network CRM. Prior to this he was the head of the eMerging Internet Technologies group at the IBM Research Center. There he built the first XML-based Search Engine. He was one of the early leaders in building XML technologies including schema-aware compression algorithms, application component generators and pattern-match systems and compilers. He built the first RDF reference implementation as a W3C standard recommendation. He led research work in other areas like domain specific search engines, multi-modal interfaces and assistive technologies, semantic transcoding, web mining, query systems, and classification for semi-structured data. Prior to this he worked on C++ compiler and runtime systems for massively parallel machines and for shared memory systems and also on retargetable compilers, program translators and generators. He has over 40 research publications and several patents to his credit. He has been a frequent speaker at several national and international technology conferences. He has advised 2 PhD and several masters dissertations. He has a degree in mathematics and a masters in computer science and engineering from the Indian Institute of Technology, and a PhD in computer science from Indiana University, Bloomington. His dissertation was on Modeling Control and Dynamic Data Parallelism in Object-Oriented Languages.