S. Sarwar

We have proposed a method based similarity level software birthmark technique to detect copy of software. Expand

Reversible logic has captured significant attention in recent time as reducing power consumption is the main concern of digital logic design. Expand

We describe a multi-task learning approach to train a Neural Machine Translation (NMT) model with a Relevance-based Auxiliary Task (RAT) for search query translation. Expand

We proposed a feature space transformation technique and classify the instances using Support Vector Machine (SVM) with its histogram intersection kernel. Expand

We present SQuID, a system for Semantic similarity-aware Query Intent Discovery. Expand

We address the role of a user in Contextual Named Entity Retrieval (CNER), showing (1) that user identification of important context-bearing terms is superior to automated approaches, and (2) that further gains are possible if the user indicates the relative importance of those terms. Expand

We propose a new dynamic trust-based similarity approach for collaborative filtering based on implicit trust information of the users, which performs better than the existing trust based recommendation algorithms. Expand

A User-User Collaborative Filtering algorithm predicts the rating of a particular item for a given user based on the judgment of other users, who are similar to the given user. Expand

We have proposed a time efficient two-stage cascaded classifier for the prediction of buy sessions and purchased items within such sessions. Expand

We propose exploring named entity recognition as a search task, where the named entity class of interest is a query and entities of that class are the relevant "documents". Expand