CHORUS Deliverable 2.2: Second report - identification of multi-disciplinary key issues for gap analysis toward EU multimedia search engines roadmap

After addressing the state-of-the-art during the first year of Chorus and establishing the existing landscape in multimedia search engines, we have identified and analyzed gaps within European research effort during our second year. In this period we focused on three directions, notably technological issues, user-centred issues and use-cases and socio- economic and legal aspects. These were assessed by two central studies: firstly, a concerted vision of functional breakdown of generic multimedia search engine, and secondly, a representative use-cases descriptions with the related discussion on requirement for technological challenges. Both studies have been carried out in cooperation and consultation with the community at large through EC concertation meetings (multimedia search engines cluster), several meetings with our Think-Tank, presentations in international conferences, and surveys addressed to EU projects coordinators as well as National initiatives coordinators. Based on the obtained feedback we identified two types of gaps, namely core technological gaps that involve research challenges, and “enablers”, which are not necessarily technical research challenges, but have impact on innovation progress. New socio-economic trends are presented as well as emerging legal challenges

Assessing the Effectiveness and Usability of Personalized Internet Search through a Longitudinal Evaluation

This paper discusses a longitudinal user evaluation of Prospector, a personalized Internet meta-search engine capable of personalized re-ranking of search results. Twenty-one participants used Prospector as their primary search engine for 12 days, agreed to have their interaction with the system logged, and completed three questionnaires. The data logs show that the personalization provided by Prospector is successful: participants preferred re-ranked results that appeared higher up. However, the questionnaire results indicated that people would prefer to use Google instead (their search engine of choice). Users would, nevertheless, consider employing a personalized search engine to perform searches with terms that require disambiguation and/or contextualization. We conclude the paper with a discussion on the merit of combining system- and user-centered evaluation for the case of personalized systems

Personalized content retrieval in context using ontological knowledge

Personalized content retrieval aims at improving the retrieval process by taking into account the particular interests of individual users. However, not all user preferences are relevant in all situations. It is well known that human preferences are complex, multiple, heterogeneous, changing, even contradictory, and should be understood in context with the user goals and tasks at hand. In this paper, we propose a method to build a dynamic representation of the semantic context of ongoing retrieval tasks, which is used to activate different subsets of user interests at runtime, in a way that out-of-context preferences are discarded. Our approach is based on an ontology-driven representation of the domain of discourse, providing enriched descriptions of the semantics involved in retrieval actions and preferences, and enabling the definition of effective means to relate preferences and context

Information Retrieval based on Content and Location Ontology for Search Engine (CLOSE)

This paper mainly focuses on the personalization of the search engine based on data mining technique, such that user preferences are taken into consideration. Clickthrough data is applied on the user profile to mine the user preferences in order to extract the features to know in which users are really interested. The basic idea behind the concept is to construct the content and location ontology2019;s, where content represent the previous search records of the user and location refer to current location of user. SpyNB is the approach used to mining the user preferences from the Clickthrough data. The ranked support vector machine (RVSM) is performed on the searched results in order to display results according to user preferences by considering Clickthrough data

Ontology-based Classification of News in an Electronic Newspaper

This paper deals with the classification of news items in ePaper, a prototype system of a future personalized newspaper service on a mobile reading device. The ePaper system aggregates news items from various news providers and delivers to each subscribed user (reader) a personalized electronic newspaper, utilizing content-based and collaborative filtering methods. The ePaper can also provide users "standard" (i.e., not personalized) editions of selected newspapers, as well as browsing capabilities in the repository of news items. This paper concentrates on the automatic classification of incoming news using hierarchical news ontology. Based on this classification on one hand, and on the users' profiles on the other hand, the personalization engine of the system is able to provide a personalized paper to each user onto her mobile reading device

Dynamically Personalizing Search Results for Mobile Users

International audienceWe introduce a novel situation-aware approach to personalize search results for mobile users. By providing a mobile user with appropriate information that dynamically satisfies his interests according to his situation, we tackle the problem of information overload. To build situation-aware user profile we rely on evidence issued from retrieval situations. A retrieval situation refers to the spatio-temporal context of the user when submitting a query to the search engine. A situation is represented as a combination of geographical and temporal concepts inferred from concrete time and location information by some ontological knowledge. User's interests are inferred from past search activities related to the identified situations. They are represented using concepts issued from a thematic ontology. We also involve a method to maintain the user's interests over his ongoing search activity and to personalize the search results