In cloud computing, documents can be outsourced to the server achieve flexible access control and efficient sharing among multiple users. The intelligently searched according some keywords with help of server. During search process, private information may leaked since contain sensitive However, existing privacy-preserving keyword schemes have high computation complexity, which are not suitable...

There exists a wide set of techniques to perform keyword-based search over relational databases but all of them match the keywords in the users’ queries to elements of the databases to be queried as first step. The matching process is a time-consuming and complex task. So, improving the performance of this task is a key issue to improve the keyword based search on relational data sources. In th...

We propose the concept of selective document retrieval (SDR) from an encrypted database which allows a client to store encrypted data on a third-party server and perform efficient search remotely. We propose a new SDR scheme based on the recent advances in fully homomorphic encryption schemes. The proposed scheme is secure in our security model and can be adapted to support many useful search f...

A CBIR is an effective way to improve the relevancy rate for image search. Image search engines such as Google and Bing mostly use keyword queried by the user and they rely on surrounding text for searching images. But sometime it is not efficient and results in imprecise output therefor ambiguity of query images is difficult to describe accurately by using keyword for e.g. Sony is query keywor...

Keyword search is a user-friendly way to query XML databases. Most previous efforts in this area focus on keyword proximity search in XML based on either tree data model or graph (or digraph) data model. Tree data model for XML is generally simple and efficient for keyword proximity search. However, it cannot capture connections such as ID references in XML databases. In the contrast, technique...

Keyword search is a user-friendly way to query XML databases. Most previous efforts in this area focus on keyword proximity search in XML based on either tree data model or graph (or digraph) data model. Tree data model for XML is generally simple and efficient for keyword proximity search. However, it cannot capture connections such as ID references in XML databases. In the contrast, technique...

Semantic web search engine Falcons support keyword based search for linked objects by using comprehensive virtual document which it creates for each object. In our work we are suggesting idea of using Selectivity Estimation of triple patterns for ranking of resulting objects and generating snippet for the keyword query for Falcons Semantic web search engine. Selectivity of a triple pattern is t...

Keyword search has traditionally focussed on retrieving documents in ranked order, given simple keyword queries. Similarly, work on keyword queries on structured data has focussed on retrieving closely connected pieces of data that together contain given query keywords. In recent years, there has been a good deal of work that attempts to go beyond the above paradigms, to improve search experien...

This paper presents a new method for building domain-specific web search engines. Previous methods eliminate irrelevant documents from the pages accessed using heuristics based on human knowledge about the domain in question. Accordingly, they are hard to build and can not be applied to other domains. The keyword spice method, in contrast, improves search performance by adding domain-specific k...

P2P network is a popular technology used for sharing and searching files on the computers connected to the network. Current search mechanisms of peer-to-peer (P2P) systems can well handle a single keyword search problem. Other than single keyword search, multi keyword search is very popular and useful in many file sharing applications. For multi keyword search, the solution which merges the res...