Hisham Mohamed
This thesis studies the scalability of the similarity search problem in large-scale multidimensional data. Similarity search, translating into the neighbour search problem, finds many applications for information retrieval, visualization, machine learning and data mining. The current exponential growth of data motivates the need for approximate and scalable algorithms. In most of existing algorithms and data-structures, […]
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Bhavneet Kaur, Sonika Jindal
CBIR is the method of searching the digital images from an image database. "Content-based" means that the search analyzes the contents of the image rather than the metadata such as colours, shapes, textures, or any other information that can be derived from the image itself. The GPU is a powerful graphics engine and a highly […]
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Zhu Lei
A tremendous amount of work has been conducted in content-based image retrieval (CBIR) on designing efficient index structure to accelerate the retrieval process. Most of them improve the retrieval efficiency via complex index structures, and few take into account the parallel implementation of algorithm on underlying hardware. It makes the existing index structures suffer from […]
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Wei Wang, Beng Chin Ooi, Xiaoyan Yang, Dongxiang Zhang, Yueting Zhuang
Multi-modal retrieval is emerging as a new search paradigm that enables seamless information retrieval from various types of media. For example, users can simply snap a movie poster to search relevant reviews and trailers. To solve the problem, a set of mapping functions are learned to project high-dimensional features extracted from data of different media […]
Dongliang Xu, Hongli Zhang, Yujian Fan
Graphics Processing Unit (GPU) has been converted to general purpose parallel processor devices from a single rendering. It performed far better than the CPU in many fields of science. String matching is widely used, especially in information retrieval, intrusion detection, Computational Biology etc. In this paper, we designed and implemented a GPU-based multi-string matching algorithm […]
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Michael J. Szaszy, Hanan Samet
The Web is constantly generating streams of textual information in the form of News articles and Tweets. In order for Information Retrieval systems to make sense of all this data partitional clustering algorithms are used to create groups of similar documents. Traditional clustering algorithms, like K-means, are not well suited for stream processing where the […]
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Mian Lu, Ge Bai, Qiong Luo, Jie Tang, Jiuxin Zhao
We present the design and implementation of GLDA, a library that utilizes the GPU (Graphics Processing Unit) to perform Gibbs sampling of Latent Dirichlet Allocation (LDA) on a single machine. LDA is an effective topic model used in many applications, e.g., classification, feature selection, and information retrieval. However, training an LDA model on large data […]
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Zheng Wei
Current trends in processor architectures increasingly include more cores on a single chip and more complex memory hierarchies, and such a trend is likely to continue in the foreseeable future. These processors offer unprecedented opportunities for speeding up demanding computations if the available resources can be effectively utilized. Simultaneously, parallel programming languages such as OpenMP […]
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Qi Zhang, Yan Wu, Zhuoye Ding, Xuanjing Huang
Content reuse is extremely common in user generated mediums. Reuse detection serves as be the basis for many applications. However, along with the explosion of Internet and continuously growing uses of user generated mediums, the task becomes more critical and difficult. In this paper, we present a novel efficient and scalable approach to detect content […]
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Nermine N. Sophoclis, M. Abdeen, El-Sayed M. El-Horbaty
Preprocessing of data is a vital aspect in information retrieval. Stemming is a major preprocessing task. The goal of stemming is to reduce the inflectional and some of the derivational forms of a word to its base form. Dealing with the massive amounts of data on the web, preprocessing generally consumes a major portion of […]
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Daniel Carlos Guimaraes Pedronette, Ricardo da S. Torres
In Content-based Image Retrieval (CBIR) systems, accurately ranking images is of great relevance, since users are interested in the returned images placed at the first positions, which usually are the most relevant ones. In general, CBIR systems consider only pairwise image analysis, that is, compute similarity measures considering only pairs of images, ignoring the rich […]
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Sandip B. Bansode
Database outsourcing as a service is a new trend emerging in the computing industry instead of managing database in-house. This introduces several security issues related to database. One of the important security requirement is privacy. A Private Information Retrieval protocol (PIR) allows user to retrieve an element from the database in such way that identity […]
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