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Featured researches published by Ben Bratu.


european conference on information retrieval | 2009

Lexical Graphs for Improved Contextual Ad Recommendation

Symeon Papadopoulos; Fotis Menemenis; Yiannis Kompatsiaris; Ben Bratu

Contextual advertising is a form of online advertising presenting consistent revenue growth since its inception. In this work, we study the problem of recommending a small set of ads to a user based solely on the currently viewed web page, often referred to as content-targeted advertising. Matching ads with web pages is a challenging task for traditional information retrieval systems due to the brevity and sparsity of advertising text, which leads to the widely recognized vocabulary impedance problem. To this end, we propose the use of lexical graphs created from web corpora as a means of computing improved content similarity metrics between ads and web pages. The results of our experimental study provide evidence of significant improvement in the perceived relevance of the recommended ads.


International Journal of Digital Multimedia Broadcasting | 2008

Two-Level Automatic Adaptation of a Distributed User Profile for Personalized News Content Delivery

Maria Papadogiorgaki; Vasileios Papastathis; Evangelia Nidelkou; Simon Waddington; Ben Bratu; Myriam Ribiere; Ioannis Kompatsiaris

This paper presents a distributed client-server architecture for the personalized delivery of textual news content to mobile users. The user profile consists of two separate models, that is, the long-term interests are stored in a skeleton profile on the server and the short-term interests in a detailed profile in the handset. The user profile enables a high-level filtering of available news content on the server, followed by matching of detailed user preferences in the handset. The highest rated items are recommended to the user, by employing an efficient ranking process. The paper focuses on a two-level learning process, which is employed on the client side in order to automatically update both user profile models. It involves the use of machine learning algorithms applied to the implicit and explicit user feedback. The systems learning performance has been systematically evaluated based on data collected from regular system users.


international workshop on semantic media adaptation and personalization | 2007

Distributed User Modeling for Personalized News Delivery in Mobile Devices

Maria Papadogiorgaki; Vasileios Papastathis; Evangelia Nidelkou; Ioannis Kompatsiaris; Simon Waddington; Ben Bratu; Myriam Ribiere

This paper presents a distributed client-server architecture for the personalized delivery of textual news content to mobile users. The user profile is distributed across client and server, enabling a high-level filtering of available content on the server, followed by matching of detailed user preferences on the handset. The high-level user preferences are stored in a skeleton profile on the server, and the low- level preferences in a detailed user profile on the handset. A learning process for the detailed user profile is employed on the handset exploiting the implicit and explicit user feedback. The systems learning performance has been evaluated based on data collected from regular system users.


mobile and ubiquitous multimedia | 2008

AQUAM: automatic query formulation architecture for mobile applications

Fotis Menemenis; Symeon Papadopoulos; Ben Bratu; Simon Waddington; Yiannis Kompatsiaris

When a user performs a web search, the first query entered will frequently not return the required information. Thus, one needs to review the initial set of links and then to modify the query or construct a new one. This incremental process is particularly frustrating and difficult to manage for a mobile user due to the device limitations (e.g. keyboard, display). We present a query formulation architecture that employs the notion of context in order to automatically construct queries, where context refers to the article currently being viewed by the user. The proposed system uses semantic metadata extracted from the web page being consumed to automatically generate candidate queries. Novel methods are proposed to create and validate candidate queries. Further two variants of query expansion and a post-expansion validation technique are described. Finally, insights into the effectiveness of our system are provided based on evaluation tests of its individual components.


Archive | 2010

METHOD AND SYSTEM FOR RECOMMENDATION OF CONTENT ITEMS

Dorothea Tsatsou; Paul C. Davis; Symeon Papadopoulos; Fotis Menemenis; Ben Bratu; George Kalfas; Ioannis Kompatsiaris


Archive | 2008

Method and apparatus for selecting advertisements and determining constraints for presenting the advertisements on mobile communication devices

Ben Bratu; Simon Waddington


Archive | 2009

SELECTION OF ASSOCIATED CONTENT FOR CONTENT ITEMS

Simon Waddington; Ben Bratu; Ioannis Kompatsiaris; Fotis Menemenis; Symeon Papadopoulos


Archive | 2007

Method and apparatus for processing a search query for text content items

Ioannis Informatics; Fotis Informatics; Evangelia Informatics; Ben Bratu; Symeon Papadopoulos; Simon Waddington


Archive | 2007

A content recommendation system and a method of operation therefor

Simon Waddington; Ben Bratu; Ioannis Kompatsiaris; Evangelia Nidelkou; Maria Papadogiorgaki; Vasileios K. Papasthathis


Archive | 2008

A content item distribution system and method of distribution therefor

Simon Waddington; David R. Bourne; Makram Bouzid; Ben Bratu

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Symeon Papadopoulos

Aristotle University of Thessaloniki

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Yiannis Kompatsiaris

Information Technology Institute

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Symeon Papadopoulos

Aristotle University of Thessaloniki

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