Feature Reduction for Product Recommendation in Internet Shopping Malls

One of the widely used methods for product recommendation in Internet shopping malls is matching product features against customers’ profiles. In this method, it is very important to choose suitable set of features for recommendation efficiency and performance, which has, however, not been rigorously researched so far. In this paper, we build a data set collected from a virtual Internet shopping experiment and adapt and apply feature reduction techniques from pattern matching and information retrieval fields to the data to analyze recommendation performance. The analysis shows that the application of SVD (Singular Value Decomposition) can be the best among the applied methods for recommendation performance

E-business in Lithuania Transport Sector: Current Situation and Challenges Ahead

Lithuania has a well-developed transportation system. Its geographically strategic position is very important to European transport corridors. In Lithuania, there are various important factors that contribute to shaping the sector’s characteristics — lack of knowledge, a low level of computerization and Internet usage – that cause ’ebusiness possibilities’ not to be used. An appropriate analysis of effective e-business usage for the development of competitive advantage between transportation companies is a very important task which requires theoretical grounding and research of practical possibilities. The purpose of paper is to analyze the use of e-business in Lithuania’s transportation companies. The survey was supposed to act as a guideline to the future of Internet usage in the Lithuanian transportation industry. The survey tried to find out considerations about the Internet, how it had affected their business and activities and what might happen in the future