In this paper, we propose a novel approach for keyword extraction. Different from previous keyword extraction methods, which identify keywords based on the document alone, this approach introduces Wikipedia knowledge and document genre to extract keywords from the document. Keyword extraction is accomplished by a classification model utilizing not only traditional word based features but also f...

Recently, keyword search has attracted a great deal of attention in XML database. It is hard to directly improve the relevancy of XML keyword search because lots of keyword-matched nodes may not contribute to the results. To address this challenge, in this paper we design an adaptive XML keyword search approach, called XBridge, that can derive the semantics of a keyword query and generate a set...

Keyword search on encrypted data enables one to search keyword ciphertexts without compromising keyword security. We further investigate this problem and propose a novel variant, dubbed certificateless keyword search on encrypted data (CLKS). CLKS not only supports keyword search on encrypted data, but also brings promising features due to the certificateless cryptography. In contrast to the ce...

Cloud computing uses internet and central remote servers to maintain data and applications. This allows much more efficient computing by centralizing storage, memory, procession and bandwidth. The data is stored in off-premises and accessing this data through keyword search. Traditional keyword search was based on plaintext keyword search. But for protecting data privacy the sensitive data shou...

Keyword extraction of scientific articles is beneficial for retrieving scientific articles of a certain topic and grasping the trend of academic development. For the task of keyword extraction for Chinese scientific articles, we adopt the framework of selecting keyword candidates by Document Frequency Accessor Variety(DF-AV) and running TextRank algorithm on a phrase network. To improve domain ...

As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud. Although traditional searchable encryption schemes allow a user to securely search over encrypted data through keywords and selectively retrieve files of interest, these techniques support only exact keyword search. In this paper, for the first time we formalize and solve the problem ...

4 Approach 2: The phone lattice keyword HMM system 10 4.1 Extraction of phone sequences . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 4.2 Keyword HMM training . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 4.3 Handling multiple keyword instances in a conversation side . . . . . . . . . . . . . . 13 4.4 Testing and scoring . . . . . . . . . . . . . ...

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...

For the automatic extraction of protein-protein interaction information from scientific articles, a machine learning approach is useful. The classifier is generated from training data represented using several features to decide whether a protein pair in each sentence has an interaction. Such a specific keyword that is directly related to interaction as "bind" or "interact" plays an important r...

Public-key Encryption with Keyword Search (PEKS) enables a server to test whether a tag from a sender and a trapdoor from a receiver contain the same keyword. In this paper, we highlight some potential security concern, i.e. a curious server is able to answer whether any selected keyword is corresponding to a given trapdoor or not (called an offline keyword guessing attack). The existing semant...