Efficient user-adaptable similarity search more and more increases in its importance for multimedia and spatial database systems. As a general similarity model for multi-dimensional vectors that is adaptable to application requirements and user preferences, we use quadratic form distance functions which have been successfully applied to color histograms in image databases [Fal+ 94]. The compone...

Finding similar users in social communities is often challenging, especially in the presence of sparse data or when working with heterogeneous or specialized domains. When computing semantic similarity among users it is desirable to have a measure which allows to compare users w.r.t. any concept in the domain. We propose such a technique which reduces the problems caused by data sparsity, espec...

Nowadays, the accumulation of people’s whereabouts due to location-based applications has made it possible to construct their mobility profiles. This access to users’ mobility profiles subsequently brings benefits back to location-based applications. For instance, in on-line social networks, friends can be recommended not only based on the similarity between their registered information, e.g., ...

This study focuses on developing the multicriteria collaborative filtering algorithm for improving the prediction accuracy. The approaches applied were user-item multirating matrix decomposition, the measurement of user similarity using cosine formula and multidimensional distance, individual criteria weight calculation, and rating prediction for the overall criteria by a combination approach. ...

This paper proposes a number of explicit and implicit ratings in product recommendation system for Business-to-customer ecommerce purposes. The system recommends the products to a new user. It depends on the purchase pattern of previous users whose purchase pattern is close to that of a user who asks for a recommendation. The system is based on weighted cosine similarity measure to find out the...

Personalized Web Search customizes the search according to the information need of the user on the Web. In Personalized Web search, search is personalized using the search results of those users profile which have the information need similar to that of present/current user. It is realized that similarity measure of the users profile is not the sufficient criterion for identifying the trusted u...

Discovering correspondences between schema elements is a crucial task for data integration. Most matching tools are semi-automatic, e.g. an expert must tune some parameters (thresholds, weights, etc.). They mainly use several methods to combine and aggregate similarity measures. However, their quality results often decrease when one requires to integrate a new similarity measure or when matchin...

We present a semantic similarity-based recommender service. Our experimental application and validation domain consists of K-12 engineering learning resources. Given a learning resource, we must determine which educational standards it addresses and vice versa, find resources that align with a given standard. One approach to this problem suggests transitively inferring standard alignment from t...

User generated content about products and services in the form of reviews are often diverse and even contradictory. This makes it difficult for users to know if an opinion in a review is prevalent or biased. We study the problem of searching for supporting opinions in the context of reviews. We propose a framework called SURF, that first identifies opinions expressed in a review, and then finds...

Defining similarity measures is a crucial task when developing CBR applications. Particularly, when employing utility-based similarity measures rather than pure distance-based measures one is confronted with a difficult knowledge engineering task. Especially if different users of a CBR system have different demands on the case retrieval this task becomes really complex and sophisticated. In suc...