Advancing community detection using Keyword Attribute Search
نویسندگان
چکیده
منابع مشابه
Attribute Truss Community Search
Recently, community search over graphs has attracted significant attention and many algorithms have been developed for finding dense subgraphs from large graphs that contain given query nodes. In applications such as analysis of protein protein interaction (PPI) networks, citation graphs, and collaboration networks, nodes tend to have attributes. Unfortunately, most previously developed communi...
متن کاملAttribute-Driven Community Search
Recently, community search over graphs has gained significant interest. In applications such as analysis of protein-protein interaction (PPI) networks, citation graphs, and collaboration networks, nodes tend to have attributes. Unfortunately, most previous community search algorithms ignore attributes and result in communities with poor cohesion w.r.t. their node attributes. In this paper, we s...
متن کاملAttribute-Based Proxy Re-Encryption with Keyword Search
Keyword search on encrypted data allows one to issue the search token and conduct search operations on encrypted data while still preserving keyword privacy. In the present paper, we consider the keyword search problem further and introduce a novel notion called attribute-based proxy re-encryption with keyword search (ABRKS), which introduces a promising feature: In addition to supporting keywo...
متن کاملA Generic Construction for Verifiable Attribute-based Keyword Search Schemes
Cloud data owners encrypt their documents before outsourcing to provide their privacy. They could determine a search control policy and delegate the ability of search token generation to the users whose attributes satisfy the search control policy. Verifiable attribute-based keyword search (VABKS) where the users can also verify the accuracy of cloud functionality is one of such schemes. In thi...
متن کاملFast community detection using local neighbourhood search
Communities play a crucial role to describe and analyse modern networks. However, the size of those networks has grown tremendously with the increase of computational power and data storage. While various methods have been developed to extract community structures, their computational cost or the difficulty to parallelize existing algorithms make partitioning real networks into communities a ch...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Journal of Big Data
سال: 2019
ISSN: 2196-1115
DOI: 10.1186/s40537-019-0243-y