International Institute of Information Technology, Hyderabad

About: International Institute of Information Technology, Hyderabad is a education organization based out in Hyderabad, India. It is known for research contribution in the topics: Authentication & Internet security. The organization has 2048 authors who have published 3677 publications receiving 45319 citations. The organization is also known as: IIIT Hyderabad & International Institute of Information Technology (IIIT).

Domain Independent Model for Product Attribute Extraction from User Reviews using Wikipedia

Abstract: The world of E-commerce is expanding, posing a large arena of products, their descriptions, customer and professional reviews that are pertinent to them. Most of the product attribute extraction techniques in literature work on structured descriptions using several text analysis tools. However, attributes in these descriptions are limited compared to those in customer reviews of a product, where users discuss deeper and more specific attributes. In this paper, we propose a novel supervised domain independent model for product attribute extraction from user reviews. The user generated content contains unstructured and semi-structured text where conventional language grammar dependent tools like parts-of-speech taggers, named entity recognizers, parsers do not perform at expected levels. We used Wikipedia and Web to identify product attributes from customer reviews and achieved F1score of 0.73.

ELKO fermions as dark matter candidates

Abstract: We study the implications of the ELKO fermions as a cold dark matter candidate. Such fermions arise in theories that are not symmetric under the full Lorentz group. Although they do not carry electric charge, ELKOs can still couple to photons through a nonstandard interaction. They also couple to the Higgs but do not couple to other standard model particles. We impose limits on their coupling strength and the ELKO mass assuming that these particles give dominant contribution to the cosmological cold dark matter. We also determine limits imposed by the direct dark matter search experiments on the ELKO-photon and the ELKO-Higgs coupling. Furthermore we determine the limit imposed by the gamma ray bursts time delay observations on the ELKO-Higgs coupling. We find that astrophysical and cosmological considerations rule out the possibility that ELKO may contribute significantly as a cold dark matter candidate. The only allowed scenario in which it can contribute significantly as a dark matter candidate is that it was never in equilibrium with the cosmic plasma. We also obtain a relationship between the ELKO self-coupling and its mass by demanding it to be consistent with observations of dense cores in the galactic centers.

Hybrid algorithms for list ranking and graph connected components

Abstract: The advent of multicore and many-core architectures saw them being deployed to speed-up computations across several disciplines and application areas. Prominent examples include semi-numerical algorithms such as sorting, graph algorithms, image processing, scientific computations, and the like. In particular, using GPUs for general purpose computations has attracted a lot of attention given that GPUs can deliver more than one TFLOP of computing power at very low prices. In this work, we use a new model of multicore computing called hybrid multicore computing where the computation is performed simultaneously a control device, such as a CPU, and an accelerator such as a GPU. To this end, we use two case studies to explore the algorithmic and analytical issues in hybrid multicore computing. Our case studies involve two different ways of designing hybrid multicore algorithms. The main contribution of this paper is to address the issues related to the design of hybrid solutions. We show our hybrid algorithm for list ranking is faster by 50% compared to the best known implementation [Z. Wei, J. JaJa; IPDPS 2010]. Similarly, our hybrid algorithm for graph connected components is faster by 25% compared to the best known GPU implementation [26].