The use of online social networks has made significant progress in recent years as the use
of the Internet has become widespread worldwide as the technological infrastructure and the …

Social applications foster the involvement of end users in Web content creation, as a result
of which a new source of vast amounts of data about users and their likes and dislikes has …

Obtaining indicators on the innovation activities of firms has been a challenge in economic
research for a long time. The most frequently used indicators-R&D expenditures and patents …

Although purchasing online has become increasingly popular, finding suitable products in
Web shop environments still requires significant effort from users. This study proposes a …

Most recommender algorithms produce types similar to those the active user has accessed
before. This is because they measure user similarity only from the co-rating behaviors …

Analyzing “what topics” a user discusses with others is important in social network analysis.
Since social relationships can be represented as multiobject relationships (eg, those …

The ability to predict the activities of users is an important one for recommender systems and
analyses of social media. User activities can be represented in terms of relationships …

Subjective assessments (SAs), such as “elegant” and “gorgeous,” are assigned to items by
users, and they are common in the reviews and tags found on many online sites. Analyzing …

Content providers want to make recommendations across multiple interrelated domains
such as music and movies. However, existing collaborative filtering methods fail to …

Tracking user interests over time is important for making accurate recommendations.
However, the widely-used time-decay-based approach worsens the sparsity problem …