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We propose “Deep Autoencoders for Feature Learning in Recommender Systems,” a novel discriminative model based on the incorporation of features from autoencoders in combination with embeddings into a deep neural network to predict ratings in ...

• A novel hybrid deep learning based recommender system ‘DNNRec’ is proposed.
• ...

We propose a novel deep learning hybrid recommender system to address the gaps in Collaborative Filtering systems and achieve the state-of-the-art predictive accuracy using deep learning. While collaborative filtering systems are ...

Mining a heterogeneous network requires measuring the relatedness between objects represented as nodes in the network. Relevance measurement on objects in a heterogeneous network is a challenging problem. Many researchers transform a heterogeneous ...

The emergence of multifarious complex networks has attracted researchers and practitioners from various disciplines. Discovering cohesive subgroups or communities in complex networks is essential to understand the dynamics of real-world systems. ...

Novel framework HeteClass is proposed for classification in heterogeneous networks.Network schema of heterogeneous network is explored to generate meta-paths.Effective weight learning method is proposed to determine weights of meta-paths.Experiments on ...

Social networking sites are used for both personal and professional interactions. Social apps thrive in the environment provided by social networking sites. Companies are focussing on this market space to promote their products and to identify new ...

Clustering is a prominent technique in data mining applications. It generates groups of data points that are similar to each other in a given aspect. Each group has some inherent latent similarity which is computed using the similarity measures. ...

Recommender Systems are used for generating recommendations for users with respect to various products and applications. Currently, recommender systems are widely used in e- commerce applications to suggest the appropriate products and services to the ...

This paper develops an automated negotiation procedure inclusive of mechanism design and agent design for bilateral multi-issue negotiations under two-sided information uncertainty. The proposed negotiation mechanism comprises a protocol called MUP (...

A system applicable in electronic commerce environments that combines the strengths of both collaborative filtering and data mining for providing better recommendations is presented. It captures the item-to-item relationship through association rule ...

In this paper, a methodology has been introduced as a decision support tool to the consumers in the Internet business. This decision support tool takes into account the multiple attributes of the product, analyses them with respect to the consumer's ...

We present, MaxDomino, an algorithm for mining Maximal Frequent Sets (MFS) for discovering association rules in dense databases. The algorithm uses novel concepts of dominancy factor and collapsibility of transaction for efficiently mining MFS. Unlike ...

We present MaxDomino, an algorithm for mining maximal frequent sets using a novel concept of dominancy factor of a transaction. We also propose a hashing scheme to collapse the database to a form that contains only unique transactions. Unlike ...

As organizations continue to deploy mission-critical, network-centric information systems, managing the security of such systems has become very critical. Building and managing such security infrastructure can be potentially very expensive, especially ...

Organizations such as NASA have vast repositories of data stored in non-relational databases. In order to access information in these environments, the queries used need to be optimized over heterogeneous (relational and non-relational) distributed ...

This paper describes the architecture of a heterogeneous distributed database management system called the Distributed Access View Integrated Database (DAVID). The DAVID system allows uniform access to distributed data stored in different DBMSs that ...

This report describes a query language based on algebra for heterogeneous databases. The database logic is used as a uniform framework for studying the heterogeneous databases. The data model based on the database logic is referred to as cluster data ...

The goal of this work is to present an advanced query processing algorithm formulated and developed in support of heterogeneous distributed database management systems. Heterogeneous distributed database management systems view the integrated data ...