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Datamining

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    An Iterative Classification Scheme for Sanitizing Large-Scale Datasets

    • B.TECH / M.TECH / M.SC / PH.D

    •  GANGADHAR.T

    • 13 Months ago

    Cheap ubiquitous computing enables the collection of massive amounts of personal data in a wide variety of domains. Many organizations aim to share such data while obscuring features that could disclose personally identifiable information.

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    Analyzing Sentiments in One Go A Supervised Joint Topic Modeling Approach

    • B.TECH / M.TECH / M.SC / PH.D

    •  GANGADHAR.T

    • 12 Months ago

    n this work, we focus on modeling user-generated review and overall rating pairs, and aim to identify semantic aspects and aspect-level sentiments from review data as well as to predict overall sentiments of reviews. We propose a novel probabilistic supervised joint aspect and sentiment model (SJASM) to deal with the problems in one go under a unified framework.

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    Collaborative Filtering-Based Recommendation of Online Social Voting

    • B.TECH / M.TECH / M.SC / PH.D

    •  GANGADHAR.T

    • 15 Months ago

    Social voting is an emerging new feature in online social networks. It poses unique challenges and opportunities for recommendation. In this paper, we develop a set of matrix-factorization (MF) and nearest-neighbor (NN)-based recommender systems (RSs) that explore user social network and group affiliation information for social voting recommendation.

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    Computing Semantic Similarity of Concepts in Knowledge Graphs

    • B.TECH / M.TECH / M.SC / PH.D

    •  GANGADHAR.T

    • 15 Months ago

    This paper presents a method for measuring the semantic similarity between concepts in Knowledge Graphs (KGs) such as WordNet and DBpedia. Previous work on semantic similarity methods have focused on either the structure of the semantic network between concepts (e.g., path length and depth), or only on the Information Content (IC) of concepts.

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    Detecting Stress Based on Social Interactions in Social Networks

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    Psychological stress is threatening people’s health. It is non-trivial to detect stress timely for proactive care. With the popularity of social media, people are used to sharing their daily activities and interacting with friends on social media platforms, making it feasible to leverage online social network data for stress detection

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    Dynamic Facet Ordering for Faceted Product Search Engines

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 13 Months ago

    Faceted browsing is widely used in Web shops and product comparison sites. In these cases, a fixed ordered list of facets is often employed. This approach suffers from two main issues. First, one needs to invest a significant amount of time to devise an effective list.

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    Efficient Keyword-Aware Representative Travel Route Recommendation

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    With the popularity of social media (e.g., Facebook and Flicker), users can easily share their check-in records and photos during their trips. In view of the huge number of user historical mobility records in social media, we aim to discover travel experiences to facilitate trip planning.

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    Mining Competitors from Large Unstructured Datasets

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 0 Months ago

    In any competitive business, success is based on the ability to make an item more appealing to customers than the competition. A number of questions arise in the context of this task: how do we formalize and quantify the competitiveness between two items Who are the main competitors of a given item

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    Continuous Top-k Monitoring on Document Streams

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 13 Months ago

    The efficient processing of document streams plays an important role in many information filtering systems. Emerging applications, such as news update filtering and social network notifications, demand presenting end-users with the most relevant content to their preferences

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    Topological Approach to Symbolic Pole-Zero Extraction Incorporating Design Knowledge

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    This paper addresses the problem of automatic analytical pole-zero extraction for multi-stage operational amplifiers with frequency compensation. Traditional methods mainly rely on numerical reference to derive approximate pole-zero expressions without incorporating any design knowledge.

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    Personal Web Revisitation by Context and Content Keywords with Relevance Feedback

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    Getting back to previously viewed web pages is a common yet uneasy task for users due to the large volume of personally accessed information on the web. This paper leverages human’s natural recall process of using episodic and semantic memory cues to facilitate recall, and presents a personal web revisitation technique.

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    Novelty Indicator for Enhanced Prioritization of Predicted Gene Ontology Annotations

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    Biomolecular controlled annotations have become pivotal in computational biology, because they allow scientists to analyze large amounts of biological data to better understand test results, and to infer new knowledge. Yet, biomolecular annotation databases are incomplete by definition, like our knowledge of biology, and might contain errors and inconsistent information.

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    Energy-efficient Query Processing in Web Search Engines

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 13 Months ago

    Web search engines are composed by thousands of query processing nodes, i.e., servers dedicated to process user queries. Such many servers consume a significant amount of energy, mostly accountable to their CPUs.

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    Clustering Data Streams Based on Shared Density between Micro-Clusters

    • B.Tech / M.Tech / M.Sc / Ph.D

    •  GANGADHAR.T

    • 12 Months ago

    As more and more applications produce streaming data, clustering data streams has become an important technique for data and knowledge engineering. A typical approach is to summarize the data stream in real-time with an online process into a large number of so called micro-clusters.

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