Although recommendation systems are the most important methods for resolving the ”information overload” problem, majority of them are beset by their inherent flaws. With the recent emergence of online social networks, the increasing social information has offered opportunities to relieve these flaws. In this paper, a new matrix factorization based social recommendation method is proposed, in wh...

There has been a surge of interest in last several years in methods for automatic generation of content indices for multimedia documents, particularly with respect to video and audio documents. As a result, there is much interest in methods for analyzing transcribed documents from audio and video broadcasts and telephone conversations and messages. The present paper deals with such an analysis ...

This paper presents context-group discrimination, a disambiguation algorithm based on clustering. Senses are interpreted as groups (or clusters) of similar contexts of the ambiguous word. Words, contexts, and senses are represented in Word Space, a high-dimensional, real-valued space in which closeness corresponds to semantic similarity. Similarity in Word Space is based on second-order co-occu...

Although much attention has recently been focused on single-subject functional networks, using methods such as resting-state functional MRI, methods for constructing single-subject structural networks are in their infancy. Single-subject cortical networks aim to describe the self-similarity across the cortical structure, possibly signifying convergent developmental pathways. Previous methods fo...

Properly structured software libraries are crucial for the success of software reuse. Specifically, the structure of the software library ought to reflect the functional similarity of the stored software components in order to facilitate the retrieval process. We propose the application of artificial neural network technology to achieve such a structured library. In more detail, we utilize an a...

We show that truth conditions for counterfactuals need not always be given in terms of a vague notion of similarity. To this end, we single out the important class of historical counterfactuals and give formally rigorous truth conditions for these counterfactuals, employing a partial ordering relation called “comparative closeness” that is defined in the framework of branching space-times. Amon...

We show that truth conditions for counterfactuals need not always be given in terms of a vague notion of similarity. To this end, we single out the important class of historical counterfactuals and give formally rigorous truth conditions for these counterfactuals, employing a partial ordering relation called “comparative closeness” that is defined in the framework of branching space-times. Amon...

In this paper, we discuss an attempt to develop an automatic language identification system for 5 closely-related Indo-Aryan languages of India – Awadhi, Bhojpuri, Braj, Hindi and Magahi. We have compiled a comparable corpora of varying length for these languages from various resources. We discuss the method of creation of these corpora in detail. Using these corpora, a language identification ...

We describe our language-independent unsupervised word sense induction system. This system only uses topic features to cluster different word senses in their global context topic space. Using unlabeled data, this system trains a latent Dirichlet allocation (LDA) topic model then uses it to infer the topics distribution of the test instances. By clustering these topics distributions in their top...

Traditionally, given two timing constraint sets, their relationship is defined by their timed trace inclusions. This approach only gives a boolean answer to if one set of constraints is contained within the other. In this paper, we first introduce a quantitative measure to describe the closeness or the similarity between two timing constraint sets. We intend to study the satisfaction bounds of ...