University of Venice, Italy - Call for application - Ph.D. program in CS (08-10)

The Department of Computer Science (Dipartimento di Informatica - http://
www.dsi.unive.it) of the University Cà Foscari of Venice has started a Ph.D. Program in 
Computer Science (http://www.unive.it/nqcontent.cfm?a_id=4868) (Dottorato di Ricerca in 
Informatica) since the academic year 2000-2001. Four full scholarships are available for 
the call for application for the next three-year program, starting on January 1st, 2008. 
The English translation of the call for application (Bando - http://www.unive.it/
nqcontent.cfm?a_id=37390) for international applicants can be found here (bando and 
extracts A http://www.unive.it/media/dipInformatica/phd/bando2007/EXTRACT_A.pdf , B 
http://www.unive.it/nqcontent.cfm?a_id=37392, C http://www.unive.it/nqcontent.cfm?
a_id=37393).
The official source is the original Bando (http://www.unive.it/nqcontent.cfm?a_id=36187).

One of the four scholarships will be funded to conduct research in the field of Web Search, 
in collaboration with Ricardo Baeza-Yates (Yahoo! Research - Barcelona - Spain, and ICREA 
Professor at the Dept. of Technology of Univ. Pompeu Fabra of Barcelona - Spain) and the 
HPC-Lab of ISTI-CNR of Pisa. Further information about this available scholarship can be 
found below.

PhD student in the field of Web Search

Title of the research: Improving efficiency and efficacy of Web Search Engines via query log 
analysis

Web Search Engines (WSEs), which have permitted users to face Web information overload, 
perhaps constitute the most important novelty of the information and communication 
technology (ICT) field in the last decade. Even if current WSEs are based on techniques of 
distributed and parallel Information Retrieval (IR), their design has created new challenges 
for researchers working in the field. One of the most important one deals with the very 
large and growing amount of information present in the Web. This large amount of 
information has called for novel IR approaches that not only improve scalability and 
efficiency of WSEs, but also the efficacy in the quality and relevance of discovered 
contents.

Moreover, despite the growing influence of current WSEs, whose distributed services are 
managed by large and important ITC industries in a centralized way, several researchers 
envision the future development of peer-to-peer (P2P) WSEs. The features of the P2P 
approach potentially offer enormous benefits for search capabilities in terms of scalability/
efficiency, resilience to failures, and dynamic managements. Additionally, such P2P WSEs 
can potentially benefit from the intellectual contributions of large user communities.

The purpose of this research is to apply Web Mining technique to the optimization of WSE 
design, both centralized and P2P, where the exploited knowledge is concerned with their 
usage by analyzing, in various ways, the logs of user queries. Note that these logs can be 
collected in several loci, on clients, WSE servers, Web servers, and proxies. The logs 
constitute a sort of secondary data derived from the user interactions with the Web and a 
WSE, while the primary data are the Web contents or the associated WSE indexes. Since we 
aim to focus on the analysis of logs, we are interested in a particular research subject in 
the area of Web Mining, called Web Usage Mining.

Among the possible applications of this research, we envision the use of query log 
analyses to modify the replacement policies of a cache that stores WSE query results. In 
this case we aim to improve the cache hit-ratio, and thus to enhance the responsiveness 
and throughput of the underlying WSE. Other possible optimizations made possible by 
these analyses concern the optimal partitioning of data (or indices) among the parallel 
servers of a WSE, aiming at reducing the amount of servers working to resolve a WSE 
query, and thus the throughput of the distributed system. We can find applications of this 
intelligent data partitioning technique for P2P WSEs. Finally, query log analyses could be 
exploited to improve the efficacy of the WSEs, for example in improving the relevance of 
the results supplied to a user. For example, an on-line analysis of logs could be used to 
discover topics that suddenly become interesting for specific communities of users. On the 
basis of such topics, we could modify the algorithms to rank the relevant results, or to 
focus the search/crawling of important data to index.



For further information about this scholarship, refer to Salvatore Orlando, sending him an 
email at [email protected]