2019-2020 Data Mining Projects for Final Year

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Data mining projects for cse students, Data mining project consultancy in bangalore, IEEE Data mining projects 2018, Data mining final year project, Data mining projects ieee, Data mining projects for cse students, Latest Data mining projects, Call:9591912372

Email: projectsatbangalore@gmail.com

  • IEEE Projects on Data Mining

    Utility mining is a new development of data mining technology. Among utility mining problems, utility mining with the itemset share framework is a hard one as no anti-monotonicity property holds with the interestingness measure. Prior works on this problem all employ a two-phase, candidate generation approach with one exception that is however inefficient and not scalable with large databases. The two-phase approach suffers from scalability issue due to the huge number of candidates. This paper proposes a novel algorithm that finds high utility patterns in a single phase without generating candidates.

  • IEEE Projects on Data science

    Social media sharing websites like Flickr allow users to annotate images with free tags, which significantly contribute to the development of the web image retrieval and organization. Tag-based image search is an important method to find images contributed by social users in such social websites. However, how to make the top ranked result relevant and with diversity is challenging. In this paper, we propose a social re-ranking system for tag-based image retrieval with the consideration of image’s relevance and diversity

  • IEEE Projects on Big Data

    —Dynamic Proof of Storage (PoS) is a useful cryptographic primitive that enables a user to check the integrity of outsourced files and to efficiently update the files in a cloud server. Although researchers have proposed many dynamic PoS schemes in singleuser environments, the problem in multi-user environments has not been investigated sufficiently. A practical multi-user cloud storage system needs the secure client-side cross-user deduplication technique, which allows a user to skip the uploading process and obtain the ownership of the files immediately, when other owners of the same files have uploaded them to the cloud server. To the best of our knowledge, none of the existing dynamic PoSs can support this technique.

2019-2020 Data mining Based Projects for CSE

big data projects for btech students

Project Code Title Technology/Year
Dm001 Integration of datamining techniques into the CBR cycle to predict the result of immunotherapy treatment Data Mining 2019
Dm002 Datamining to Alert the Formation of Women Objectification Stereotypes in Video Games Data Mining 2020
Dm003 A Review on Dimensionality Reduction for Multi-label Classification Data Mining 2019
Dm004 Features of the Design Operating Unit Inference Engine and Its Implementation on FPGA Data Mining 2020
Dm005 Detection of Online Manipulation to Prevent Users Victimization Data Mining 2019
Dm006 Analysis models of technical and economic data of mining enterprises based on big data analysis Data Mining 2019
Dm007 Data Mining Library for Big Data Processing Platforms: A Case Study-Sparkling Water Platform Data Mining 2019
Dm008 PPSF: An Open-Source Privacy-Preserving and Security Mining Framework Data Mining 2019
Dm009 Applications of Stream Data Mining on the Internet of Things: A Survey A Multi-objective Rule Optimizer with an Application to Risk Management Data Mining 2019
Dm0010 Privacy-Preserving Frequent Pattern Mining from Big Uncertain Data Data Mining 2019


2019 Data mining projects for cse students

1.A New Query Recommendation Method Supporting Exploratory Search Based on Search Goal Shift Graphs

2.Approximate Order-Sensitivek-NN Queries over Correlated High-Dimensional Data

3.BEATS: Blocks of Eigenvalues Algorithm for Time Series Segmentation

4.Classifier Ensemble by Exploring Supplementary Ordering Information

5.Efficient Detection of Overlapping Communities Using Asymmetric Triangle Cuts

6.High-Order Proximity Preserved Embedding for Dynamic Networks

7.Identifying Genetic Risk Factors for Alzheimer's Disease via Shared Tree-Guided Feature Learning Across Multiple Tasks

8.NHAD: Neuro-Fuzzy Based Horizontal Anomaly Detection in Online Social Networks

For More Info Contact:9591912372

Data mining projects using Java

2019-2020 IEEE Projects for CSE Based on Data Mining

2018-Privacy Policy Inference of User-Uploaded Images on Content Sharing Sites
Abstract—With the increasing volume of images users share through social sites, maintaining privacy has become a major problem, as demonstrated by a recent wave of publicized incidents where users inadvertently shared personal information. In light of these incidents, the need of tools to help users control access to their shared content is apparent. Toward addressing this need, we propose an Adaptive Privacy Policy Prediction (A3P) system to help users compose privacy settings for their images. We examine the role of social context, image content, and metadata as possible indicators of users’ privacy preferences. We propose a two-level framework which according to the user’s available history on the site, determines the best available privacy policy for the user’s images being uploaded. Our solution relies on an image classification framework for image categories which may be associated with similar policies, and on a policy prediction algorithm to automatically generate a policy for each newly uploaded image, also according to users’ social features. Over time, the generated policies will follow the evolution of users’ privacy attitude. We provide the results of our extensive evaluation over 5,000 policies, which demonstrate the effectiveness of our system, with prediction accuracies over 90 percent.

2019-2020 IEEE Projects for cse in Data Mining

2018-Context-based Diversification for Keyword Queries over XML Data

Abstract—While keyword query empowers ordinary users to search vast amount of data, the ambiguity of keyword query makes it difficult to effectively answer keyword queries, especially for short and vague keyword queries. To address this challenging problem, in this paper we propose an approach that automatically diversifies XML keyword search based on its different contexts in the XML data. Given a short and vague keyword query and XML data to be searched, we firstly derive keyword search candidates of the query by a simple feature selection model. And then, we design an effective XML keyword search diversification model to measure the quality of each candidate. After that, two efficient algorithms are proposed to incrementally compute top-k qualified query candidates as the diversified search intentions. Two selection criteria are targeted: the k selected query candidates are most relevant to the given query while they have to cover maximal number of distinct results. At last, a comprehensive evaluation on real and synthetic datasets demonstrates the effectiveness of our proposed diversification model and the efficiency of our algorithms.


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