A Conceptual Framework for Enhancing Product Search with Product Information from Reviews

Product search today is limited, as users can only search and filter for a restricted set of product features, e.g. 15” and 1TB hard disk when searching for a laptop. The often decision- critical aspects of a product are however hidden in user reviews (“noisy fan” or “bright display”) and are not available until a product has been found. This paper proposes a conceptual framework for the integration of product aspects, that have been mined and derived from consumer reviews, into the product search. The framework structures the challenges that arise in four major fields and gives an overview of existing research for each one of them: Data challenges, user experience challenges, purchase process challenges and business challenges. It may inform researchers from various disciplines to perform target-oriented research as well as practitioners what to consider when building up such an enriched product search

Iterative Voting, Control and Sentiment Analysis

In multi-agent systems agents often need to take a collective decision based on the preferences of individuals. A voting rule is used to decide which decision to take, mapping the agents' preferences over the possible candidate decisions into a winning decision for the collection of agents. In these kind of scenarios acting strategically can be seen in two opposite way. On one hand it may be desirable that agents do not have any incentive to act strategically. That is, to misreport their preferences in order to influence the result of the voting rule in their favor or acting on the structure of the election to change the outcome. On the other hand manipulation can be used to improve the quality of the outcome by enlarging the consensus of the winner. These two different scenarios are studied in this thesis. The first one by modeling and describing a natural form of control named ``replacement control'' and characterizing for several voting rules its computational complexity. The second scenario is studied in the form of iterative voting frameworks where individuals are allowed to change their preferences to change the outcome of the election. Computational social choice techniques can be used in very different scenarios. This work reports a first attempt to introduce the use of voting procedures in the field of sentiment analysis. In this area computer scientists extract the opinion of the community about a specific item. This opinion is extracted aggregating the opinion expressed by each individual which leaves a text in a blog or social network about the given item. We studied and proposed a new aggregation method which can improve performances of sentiment analysis, this new technique is a new variance of a well-known voting rule called Borda