Online Subgraph Skyline Analysis Over Knowledge Graphs - 2016


Subgraph search is terribly useful in several real-world applications. However, users might be overwhelmed by the lots of matches. In this paper, we have a tendency to propose a subgraph skyline analysis drawback, denoted as S2A, to support more sophisticated analysis over graph information. Specifically, given a massive graph G and a query graph q, we tend to want to seek out all the subgraphs g in G, such that g is graph isomorphic to q and not dominated by any different subgraphs. So as to improve the potency, we devise a hybrid feature encoding incorporating each structural and numeric features based on a partitioning strategy, and discuss a way to optimize the area partitioning. We tend to additionally gift a skylayer index to facilitate the dynamic subgraph skyline computation. Moreover, an attribute cluster-primarily based methodology is proposed to deal with the curse of dimensionality. In depth experiments over real datasets make sure the effectiveness and efficiency of our algorithm.

Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Classification of Online Toxic Comments Using Machine Learning Algorithms ABSTRACT: Toxic comments are online remarks that are insulting, abusive, or inappropriate, and frequently cause other users to quit a
PROJECT TITLE : Reviewer Credibility and Sentiment Analysis Based User Profile Modelling for Online Product Recommendation ABSTRACT: Even for humans, deciphering user buying preferences, likes and dislikes is a difficult undertaking,
PROJECT TITLE : Active Learning From Imbalanced Data A Solution of Online Weighted Extreme Learning Machine ABSTRACT: Active learning is well known for its ability to improve the quality of a classification model while also reducing
PROJECT TITLE : Online ADMM-based Extreme Learning Machine for Sparse Supervised Learning ABSTRACT: In the field of machine learning, sparse learning is a useful strategy for selecting features and avoiding overfitting. An online
PROJECT TITLE : Online Subspace Learning from Gradient Orientations for Robust Image Alignment ABSTRACT: Robust and effective picture alignment remains a difficult task due to the size and complexity of images as well as fluctuations

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry