Ville Ollikainen

A new similarity measure using Bhattacharyya coefficient for collaborative filtering in sparse data

Collaborative filtering (CF) is the most successful approach for personalized product or service recommendations. Neighborhood based collaborative filtering is an important class of CF, which is simple, intuitive and efficient product recommender system widely used in commercial domain. Typically, neighborhood-based CF uses a similarity measure for finding similar users to an active user or similar products on which she rated. Traditional similarity measures utilize ratings of only co-rated items while computing similarity between a pair of users. Therefore, these measures are not suitable in a sparse data. In this paper, we propose a similarity measure for neighborhood based CF, which uses all ratings made by a pair of users. Proposed measure finds importance of each pair of rated items by exploiting Bhattacharyya similarity. To show effectiveness of the measure, we compared performances of neighborhood based CFs using state-of-the-art similarity measures with the proposed measured based CF. Recommendation results on a set of real data show that proposed measure based CF outperforms existing measures based CFs in various evaluation metrics.

`Podracing': experimenting with mobile TV content consumption and delivery methods

Recently, mobile TV has been launched in several countries. While mobile TV integrates television contents into mobile phones, the most personal of communication devices, it becomes interesting to know how this feature will be used throughout the day and in varying contexts of everyday life. This paper presents empirical results on the use of mobile TV with different delivery mechanisms and both quantitative and qualitative results on how end-users prefer to use mobile TV contents in different situations. The data is based on ongoing empirical research in Finland in 2006 and 2007. The mobile TV services under study included both news and entertainment contents, and were tested in 3G, DVB-H and Wi-Fi networks using different delivery paradigms: broadcast, on-demand and download. To explore the use of different delivery methods and content consumption, we have developed a mobile TV service protoype, called Podracing. The analysis shows that users appreciated up-to-date information and information-rich media forms and contents especially for mobile news delivery. There was high demand for only the latest news on mobiles. The real-time property was considered important. Most of the users looked at the headlines or followed the news several times a day – much more often than the traditional TV and news prime times would allow.

Exploiting Bhattacharyya Similarity Measure to Diminish User Cold-Start Problem in Sparse Data

Collaborative Filtering (CF) is one of the most successful approaches for personalized product recommendations. Neighborhood based collaborative filtering is an important class of CF, which is simple and efficient product recommender system widely used in commercial domain. However, neighborhood based CF suffers from user cold-start problem. This problem becomes severe when neighborhood based CF is used in sparse rating data. In this paper, we propose an effective approach for similarity measure to address user cold-start problem in sparse rating dataset. Our proposed approach can find neighbors in the absence of co-rated items unlike existing measures. To show the effectiveness of this measure under cold-start scenario, we experimented with real rating datasets. Experimental results show that our approach based CF outperforms state-of-the art measures based CFs for cold-start problem.

Electronic editor: automatic content-based sequential compilation of newspaper articles

Abstract New information carriers, such as electronic books and MP3 players, can be utilized for displaying customized content. Using these carriers, however, only browsing forwards and backwards is easy. The crucial question in making these carriers user-friendly is then to construct an order of presentation that enhances readability. We have developed a tool that uses the self-organizing map algorithm of Kohonen to automatically organize a collection of text articles into a meaningful content-based sequential order. The article sequence constructed by the system was compared to the sequences made by 21 humans, and in our small-scale case study they were comparable.

Comparing media types and delivery methods on mobile terminals

If a user had a choice of watching the latest television news on the mobile phone, or listening to the news on the radio, or reading text news with the mobile, what would he choose? The project conducted three trials, in which mobile terminals were used in such a variety of situations that no single media type and no delivery method was able to fulfill all needs. Unlike previous studies, the results indicate that mobile television does not involve low commitment: The users did not usually do anything else while watching. Furthermore, just surfing around or viewing an arbitrary program flow seems not to be enough. Even though one of key motives of mobile television use is to kill time, people may want to kill time with content which is appropriate for that particular moment. Entertainment in mobile broadcast content was found problematic, because mobile viewing is typically short-term and fragmentary; thus the users often missed the beginnings of episodes.

Stereoscopic 3-D TV webcast

With limited RF bandwidth, terrestrial stations are constrained by the current state of consumer TV receivers in the home to manage the high computation and bandwidth demands for 3DTV. This paper presents an experiment of delivering stereoscopic 3DTV on-demand content over HTTP network. Our approach makes use of the newest adaptive streaming mechanism for webcasting 3D to individual TV users. The goal was to explore whether HTTP network can or does transport HD quality stereoscopic 3DTV using a desktop computer for 3D decoding and how far it is from the reality. Ultimately, we seek to conclude and to present the problems we met and potential research on webcasting of advanced multi-view 3DTV.