00596nas a2200133   4500008004100000245010300041210006900144260001900213300001300232100002100245700002600266700002800292856014200320       2011                        eng d00aLearning from user's behavior - A technique for personalized news search supporting result cashing0 aLearning from users behavior A technique for personalized news s  biConcept Press  a 177-1961 aBouras, Christos1 aPoulopoulos, Vassilis1 aSilintziris, Panagiotis  uhttp://telematics.upatras.gr/telematics/publications/learning-users-behavior-technique-personalized-news-search-supporting-result-cashing01776nas a2200145   4500008004100000245004300041210004100084260001700125300001000142520130900152100002101461700002601482700002801508856009401536       2009                        eng d00aDate - based dynamic caching mechanism0 aDate based dynamic caching mechanism  cJune 18 - 20  a67-743 aNews portals based on the RSS protocol are becoming nowadays one of the dominant ways that Internet users follow in order to locate the information they are looking for. Search engines, which operate at the back-end of a big portion of these web sites, receive millions of queries per day on any and every walk of web life. While these queries are submitted by thousands of unrelated users, studies have shown that small sets of popular queries account for a significant fraction of the query stream. A second truth has to do with the high frequency that a particular user tends to submit the same or highly relative search requests to the engine. By combining these facts, in this paper, we design and analyze the caching algorithm deployed in our personalized RSS portal, a web-based mechanism for the retrieval, processing and presentation in a personalized view of articles and RSS feeds collected from major Internet news portals. By using moderate amounts of memory and little computational overhead, we achieve to cache query results in the server, both for personalized and non-personalized user searches. Our caching algorithm operates not in a stand-alone manner but it co-operates and binds with the rest of the modules of our Portal in order to accomplish maximum integration with the system.1 aBouras, Christos1 aPoulopoulos, Vassilis1 aSilintziris, Panagiotis  uhttp://telematics.upatras.gr/telematics/publications/date-based-dynamic-caching-mechanism01805nas a2200145   4500008004100000245006500041210006300106260001600169300001500185520127400200100002101474700002601495700002801521856011001549       2009                        eng d00aPersonalized News Search in WWW: Adapting on user's behavior0 aPersonalized News Search in WWW Adapting on users behavior  c24 - 28 May  a 125 - 1303 aPersonalized Web Search becomes nowadays a
promising option in the field of Information Retrieval and
search engines design by improving both output quality and
user experience. In this paper, we present and evaluate the
subsystem, which conducts the Advanced and Personalized
search of PeRSSonal, a web-based mechanism for the retrieval,
processing and presentation of articles and RSS feeds collected
from major news portals of the Internet. The proposed
technique uses information explicitly provided by the user in
his profile as well as information that the mechanism can learn
from the user?s behavior during his search and browsing
sessions in the system. As this behavior dynamically evolves,
the same happens to the user?s interests under the prism of the
search engine. By adopting this user-centric approach, we
manage to present the user with better-refined and more
focused results, incorporating his personal preferences to the
output. The algorithm operates not in a stand-alone manner
but it co-operates and binds with the rest of modules of
PeRSSonal in order to accomplish maximum integration with
the system. Furthermore, we introduce an enhancement in the
search function, based on cached results from past search
sessions of each user individually.1 aBouras, Christos1 aPoulopoulos, Vassilis1 aSilintziris, Panagiotis  uhttp://telematics.upatras.gr/telematics/publications/personalized-news-search-www-adapting-users-behavior