advertising in order to improve the consumer’s online experience. We segregate keyphrases from a dataset covering thirty-three consecutive months from a major US retailer consisting of 7 million daily records of a real time keyword advertising campaign into three gender categories (male, female and neutral) each with two groups
In cloud storage environment, clients no longer have physical possession of their data, it indicates that their data may be leaked maliciously by cloud provider. To avoid the security risks, we propose a privacy preserving keyword searching scheme whose encryption procedure needs no pairing operation. Our scheme
Keyword Search Over Relational Databases(KSORD) has been widely studied in recent years. However, existing KSORD methods are usually based on schema graph or data graph and they are actually tuple-level methods. That is, the retrieved objects are direct tuple-level relational data, and the retrieval results are tuple
The advent of cloud computing has dramatically changed the IT scene, as it offers cost savings and improvements to major operations. Nevertheless, the major obstacle relies on the effort on how to secure sensitive data files that are outsourced to the cloud environment. To ensure confidentiality, the sensitive data
The remote storage service has been one of the most popular cloud services. However, outsourcing in the remote storage causes a privacy issue such as the exposure of personal data and the leakage of private information. In this paper, we focus on the encrypted keyword search problem, called searchable symmetric
cloud becomes a major challenge. The public-key encryption with keyword search (PEKS) scheme and many of its variants have been proposed to respond to this challenge. However, given a large number of data (or searchable keywords) would be tested sequentially in these PEKS schemes, previous search results should be employed
Recently, Li et al. introduced a fuzzy keyword search over encrypted data in Cloud Computing. Their approach relies on fuzzy keyword sets which are used by a symmetric searchable encryption protocol. The idea behind these fuzzy keyword sets is to index – before the search phase – the exact keywords but also the
In online social networks (OSNs), user connections can be represented as a network. The network formed has distinct properties that distinguish it from other network topologies. In this work, we consider an unstructured keyword based social network topology where each edge has a trust value associated with it to
particular category. Search is truly ``local'' in the sense that keyword relevance is not global, but specific to the category. In contrast to using a search engine, users can guide the exploration engine with relevance feedback alone without entering keywords.
Health Literature (CINAHL), Medline, and online reference sources.
Review MethodsLiterature review was guided by using the keywordtrust. Further contextual explication was done by adding a review of literature from sociology and history regarding the evolution of African
Keywords offers a conversational journey through the overlying terrains of politically engaged art and artistically engaged politics, combining a major statement on subversive aesthetics, a survey of radical film strategies, and a lexicon of over a thousand terms and concepts.
No other book combines an ambitious essay on radical politics and aesthetics in film with a lexicon of terms and ideas,...
relevance of results by combining topic-specific trust among community members and individual's resources evaluation. The approach has been prototyped with Antu, built over the IT-specific faceted keyword-based search tool Yarquen. An experimental study was conducted with informatics graduate students, and found improved
) covers all applications of anonymous encryption, fully private communication and search on encrypted data, which provide trusted data access control policy to CSP. However, the existing works only achieve either selectively attribute-hiding or adaptively attribute-hiding under some strong assumptions in the public key
proteins based on the experimentally validated interactions curated in public PPI database. Additionally, we have tried to provide the information on interaction types associated with each of the predicted interactions with an estimated confidence. Further, we have analyzed our predicted interactions by finding overlap with
Most of the Image Search Engines suffer from the lack of comprehensive image model capturing semantic richness and the conveyed signal information. Instead, they rely on the text information that is associated with the images like their names, surrounding text, etc. As a consequence, the retrieval results may
combining the genetic algorithm with biological information extracted from the KEGG database. A comparative study is carried out over public data from three different types of cancer (leukemia, lung cancer and prostate cancer). Even though the analyses only use features having KEGG information, the results demonstrate that
provide sustainable solutions, often with only very limited information. This paper focuses on the themes of “disaster management”, “natural hazards” and “simulation”, aiming to identify current research trends using bibliometric analysis. This analysis technique combines quantitative and statistical methods to identify
design principles, namely Write-Once Partitioning, Linear Pipelining and Background Linear Merging, and show how they can be combined to produce an embedded search engine matching the hardware constraints of secure tokens and reconciling high insert/delete/update rate and query scalability. Our experimental results
The combination of manual curation and the reliance on updates from submitters to the public sequence databases is currently inefficient and impedes the comprehensive and timely release of records with new taxonomic names. This should be improved by making several steps during data release more efficient. This
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.