Sergiu Gordea

Comparing Recommendation Strategies in a Commercial Context

From an industrial perspective, recommender systems constitute the base technology for providing interactivity and personalization in electronic business-to-consumer marketplaces. Robin Burke distinguishes between five different recommendation techniques: collaborative, content based, utility based, demographic, and knowledge based.

etPlanner: An IT Framework for Comprehensive and Integrative Travel Guidance

Recommender systems in travel industry make helpful and persuasive product and service suggestions and thus reduce the burden of information overload and domain complexity for users. Within the scope of the etPlanner project we innovate existing technology by considering all trip phases and by supporting next to standard Web interfaces also different mobile devices.

Improving Europeana search experience using query logs

Europeana is a long-term project funded by the European Commission with the goal of making Europes cultural and scientific heritage accessible to the public. Since 2008, about 1500 institutions have contributed to Europeana, enabling people to explore the digital resources of Europes museums, libraries and archives. The huge amount of collected multi-lingual multi-media data is made available today through the Europeana portal, a search engine allowing users to explore such content through textual queries. One of the most important techniques for enhancing users search experience in large information spaces, is the exploitation of the knowledge contained in query logs. In this paper we present a characterization of the Europeana query log, showing statistics on common behavioral patterns of the Europeana users. Our analysis highlights some significative differences between the Europeana query log and the historical data collected by general purpose Web Search Engine logs. In particular, we find out that both query and search session distributions show different behaviors. Finally, we use this information for designing a query recommendation technique having the goal of enhancing the functionality of the Europeana portal.

Time filtering for better recommendations with small and sparse rating matrices

The recommendation technologies are used as viable solutions for advertising the best products and for helping users to orientate themselves in large e-commerce platforms offering various product assortments. Despite their popularity they still suffer of cold start and sparse data matrices limitations, which affect seriously the effectiveness of recommenders employed in applications with less user-system interaction. Having the aim to improve the quality of recommendation lists in such systems we introduce time heuristics into the recommendation process and propose two new variants of collaborative filtering algorithms for solving these problems. A time aware method is proposed for making more correct evaluations of recommenders used in domains with strong time dependencies.

A hybrid similarity concept for browsing semi-structured product items

Personalization, information filtering and recommendation are key techniques helping online-customers to orientate themselves in e-commerce environments. Similarity is an important underlying concept for the above techniques. Depending on the representation mechanism of information items different similarity approaches have been established in the fields of information retrieval and case-based reasoning. However, many times product descriptions consist of both, structured attribute value pairs and free-text descriptions. Therefore, we present a hybrid similarity approach from information retrieval and case-based recommendation systems and enrich it with additional knowledge-based concepts like threshold values and explanations. Furthermore, we implemented our hybrid similarity concept in a service component and give evaluation results for the e-tourism domain.

Measuring, monitoring and controlling software maintenance efforts

Launching a new software product on the market and maximizing the profit obtained from it is already an art considering the high expectations and conflicting requirements of the software market. Product managers have to take tough decisions regarding the product life cycle like choosing the right moment for a new release, modernization or system replacement. Under these conditions they have to continually monitor the time evolution of efforts and costs required for implementing and maintaining the software product. Software tools that are able to assess these activities constitute a great value for those who need to take product management decisions. In this paper we present an approach for measuring and monitoring maintenance efforts by focusing on measurements of coding related activities. We employ data mining techniques for classifying coding related effort and present a preliminary evaluation of using this approach

An Image Similarity Search for the European Digital Library and Beyond

This paper presents an Image Similarity Search service for the European Digital Library and summarizes the requirements of different stakeholders that make use of this kind of service. The current implementation is suited to support public users when exploring the content of Europeana. Further enhancements of this service are required to support design related activities by stimulating and inspiring the creativity of professional designers.

When entities meet query recommender systems: semantic search shortcuts

The Web of Data is growing in popularity and dimension, and entities are gaining importance in many research fields. In this paper, we explore the use of entities that can be extracted from a query log to enhance query recommendation. In particular, we use a large query log recorded by the Europeana portal, a central access point to the descriptions of more than 20 million cultural heritage objects, and we extend a state-of-the-art query recommendation algorithm to take into account the semantic information associated with the submitted queries. Our novel method generates highly related and diversified suggestions. We assess it by means of a new evaluation technique. The manually annotated dataset used for performance comparisons has been made available to the research community to favor the repeatability of the experiments.

Metadata enrichment services for the europeana digital library

We demonstrate a metadata enrichment system for the Europeana digital library. The system allows different institutions which provide to Europeana pointers (in the form of metadata records - MRs) to their content to enrich their MRs by classifying them under a classification scheme of their choice, and to extract/highlight entities of significant interest within the MRs themselves. The use of a supervised learning metaphor allows each content provider (CP) to generate classifiers and extractors tailored to the CPs specific needs, thus allowing the tool to be effectively available to the multitude (2000+) of Europeana CPs.

The Europeana Sounds Music Information Retrieval Pilot

This paper describes the realization of a Music Information Retrieval (MIR) pilot for a huge audio corpora of European cultural sound heritage, which was developed as part of the Europeana Sounds project. The demonstrator aimed at evaluating the applicability of technologies deriving from the MIR domain to content provided by various European digital libraries and audio archives. To approach this aim, a query-by-example functionality was implemented using audio-content based similarity search. The development was preceded by an elaborated evaluation of the Europeana Sounds collection to assess appropriate combinations of music content descriptors that are capable to effectively discriminate the various types of audio-content provided within the dataset. The MIR-pilot was evaluated both by using an automatic and a user based evaluation. The results showed that the quality of the implemented query-by-example algorithm is comparable to state-of-the-art music similarity approaches reported in literature.