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Online searching of books have gained astounding popularity worldwide. It has also attracted variety of researchers globally. Searching of books (e.g. Amazon.com, aNobii, LibraryThing etc) with the help of Social metadata(e.g. tags, reviews) and professional metadata (e.g. ISBN Number, Title, Publisher) is gradually becoming a sizzling hot topic under the aegis of Information Retrieval. In this paper,...
Efficiently answering XML keyword queries has attracted much research effort in the last decade. The key factors resulting in the inefficiency of existing methods are the common-ancestor-repetition (CAR) and visiting-useless-nodes (VUN) problems. To address the CAR problem, we propose
This paper describes a mechanism of defining keywords on our Information Utilization System, which we have proposed to utilize information received via e-mail. Our system utilizes metadata of e-mail messages to organize pieces of information, and keywords are used to classify pieces of information based on their
A solution of a keyword query over graphs is a Group Steiner tree, which is rooted at a node and whose nodes collectively satisfy the query (e.g. node keywords cover all the query keywords), and in which the sum of edge weights satisfies given conditions (e.g., need to be minimum or be the first K minimal among all
One of the most convenient ways to query XML data is a keyword search because it does not require any knowledge about XML structure and without the need to learn a new user interface. However, keyword search interface is very flexible. It is hard for a system to decide which node is likely to be chosen as a return
Recently, a great deal of attention has been focusing on processing keyword search over static and XML streams. Keyword search is becoming more popular for its simplicity and its user-friendliness in querying XML databases. However, it is hard to express real search intention with just keyword search. There are many
approach, personal data are uniformly represented in a single data model proposed in this paper, and stored in a data warehousing system based on a storage model corresponding to the data model. Then, users are enabled to easily retrieve all their personal information by using keywords or a semi-structured query language.
In the age of Internet, with the online information explosive growth, people want to find information we need in the cyberworld fleetly and exactly. The information retrieval method based on the keyword or the simple logic-combination of the keywords has been unable to meet the people's need of information getting to
This paper presents metadata extraction technique from email documents. Emails are characterized in terms of keywords that are extracted from body of the mail using frequency, average similarity and term discrimination value measures. The email metadata is defined as a document type definition (DTD) in extensible
Because of ignoring the semantic information inside the keywords, the traditional searching engine based on the key words has low recall and precision. Aiming at this, some semantic retrieval system design ideas and the retrieval process are proposed in this paper.The key technologies-related in semantic retrieval
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