Beyond the Stars: Improving Rating Predictions using Review Text Content
Amélie Marian, Institute: Rutgers University, Etats-Unis
Date: Jeudi 24 septembre 14h00
Lieu: LIP6, salle 847
Slides: Attach:AmelieMarian_Beyond_the_Stars-0909.pdf
RESUME Online reviews are an important asset for users deciding to buy a product, see a movie, or go to a restaurant, as well as for businesses tracking user feedback. However, most reviews are written in a free-text format, and are therefore difficult for computer systems to understand, analyze, and aggregate. One consequence of this lack of structure is that searching text reviews is often frustrating for users; keyword searches typically do not provide good results as the same keywords routinely appear in good and in bad reviews. User experience would be greatly improved if the structure and sentiment information conveyed in the content of the reviews were taken into account. Our work focuses on identifying this structure and sentiment information from free-text reviews, and using this knowledge to improve user experience in accessing reviews. Specifically, we focused on improving recommendation accuracy in a restaurant review scenario.
We report on our classification effort, and on the insight on user-reviewing behavior that we gained in the process. We propose new ad-hoc and regression-based recommendation measures, that both take into account the textual component of user reviews. Our results show that using textual information results in better general or personalized restaurant score predictions than those derived from the numerical star ratings given by the users.
Schema Mapping and Query Translation in Heterogeneous XML P2P Databases
Angela Bonifati, CNR, Italie
Date: Jeudi 24 septembre 14h00
Lieu: LIP6, salle 847
Slides : Attach:Angela_LIP6_24_09_2009.pdf
RESUME Peers in a peer-to-peer data management system often have heterogeneous schemas and no mediated global schema. To translate queries across peers, we assume each peer provides correspondences between its schema and a small number of other peer schemas. We focus on query reformulation in the presence of heterogeneous XML schemas, including data–metadata conflicts. We develop an algorithm for inferring precise mapping rules from informal schema correspondences. We define the semantics of query answering in this setting and develop query translation algorithm. Our translation handles an expressive fragment of XQuery and works both along and against the direction of mapping rules. We describe the HePToX heterogeneous P2P XML data management system which incorporates our results. We report the results of extensive experiments on HePToX on both synthetic and real datasets. We demonstrate our system utility and scalability on different P2P distributions.
Joint work with Elaine Chang, Terence Ho, Laks V.S. Lakshmanan, Rachel Pottinger and Yongik Chung