The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
This paper proposes a strategy of the summary sentence selection for query-focused multi-document summarization through extracting keywords from relevant document set. It calculates the query related feature and the topic related feature for every word in relevant document set, then obtains the importance of the word
Path and Keyword search in XML documents has recently become an active area of research, in which constructing an effective index is a key issue. Existing index structures and encoding schemes for XML query processing target the Parent-Child and Ancestor-Descendant relationships, however, they depend on large index
Keyword search over relational databases (KSORD) enables casual users to use keyword queries (a set of keywords) to search relational databases just like searching the Web, without any knowledge of the database schema or any need of writing SQL queries. In KSORD, retrieval of user's initial query is often unsatisfying
Recently, with the amount of available textual data in spatial databases growing rapidly, more and more applications are required to support both spatial joins and keyword-based text information retrieval. In this paper, we discuss a new type of query, called as SJIRKS, which efficiently integrates spatial join on
Most educational resource grids are required to support multi-attribute multi-keyword fuzzy-matching queries. But such queries are not efficiently supported in current structured P2P systems. Towards an efficient P2P system capable of processing multi-attribute multi-keyword fuzzy-matching queries with high recall
Precision queries of keyword search developed quickly over relational databases, but it can't be better to process fuzzy queries for satisfying higher requests of users. Aiming at fuzzy queries of numerical attributes for keyword-based search over relational databases, we give a new kind of membership function (normal
KSORD (keyword search over relational database) techniques allow users to obtain information from databases, which is just like using search engines. However, the advanced techniques only realize exact queries, but not for fuzzy queries. The Rocchio algorithm of learning classification is introduced which is made a
Keyword queries enjoy widespread usage as they represent an intuitive way of specifying information needs. Recently, answering keyword queries on graph-structured data has emerged as an important research topic. The prevalent approaches build on dedicated indexing techniques as well as search algorithms aiming at
This work addresses a novel spatial keyword query called the m-closest keywords (mCK) query. Given a database of spatial objects, each tuple is associated with some descriptive information represented in the form of keywords. The mCK query aims to find the spatially closest tuples which match m user-specified keywords
Nowadays the existing search engines are always lack of the consideration of personalization. They display the same search results for different users despite their differences in interesting and purpose. In order to solve this problem, this paper introduces a new method of using keyword query series to express the
Keyword search provides a simple yet effective way for the users to query and explore the underlying documents. In the recent years, there have been a great deal of research and development activities on extending keyword search capabilities to handle relational data, the dominant form in which business data are
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs. Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
The relevance feedback techniques have been studied in the field of document retrieval, aiming to generate appropriate queries for userspsila information needs.Conventional relevance feedback techniques are performed on document space, while the resultant queries should be represented in keyword space. In this paper
Query-recommendation systems based on inputted queries have become widespread. These services are effective if users cannot input relevant queries. However, the conventional systems do not take into consideration the relevance between recommended queries. This paper proposes a method of obtaining related queries and clustering them by using the history of query frequencies in query logs. We define...
the interfaces of web services, we make operations defined in WSDL files which compose web services as the base units for searching and organize all information of operations and corresponding components as documents, which will facilitate IR-Style keyword searching. In order to improve the precision of searching, we
retrieval scheme based on annotation keywords and visual content, which can benefit from the strength of text- and content-based retrieval. The system starts query triggered by some keywords, and further refines the retrieval result based on blobs and regions information. The first step is to complete semantic filtering with
Efficient discovery of information based on partially specified and misspelled query keywords is a challenging problem in large scale peer-to-peer (P2P) networks. This paper presents QPM, a P2P search mechanism for efficient information retrieval with misspelled and partial keywords. QPM uses the double metaphone
needs. In this paper, we present the design, architecture and implementation of an open-source keyword-based paradigm for the search of software resources in Grid infrastructures, called Minersoft. A key goal of Minersoft is to annotate automatically all the software resources with keyword-rich metadata. Using advanced
A previously proposed keyword search paradigm produces, as a query result, a ranked list of object summaries (OSs); each OS summarizes all data held in a relational database about a particular data subject (DS). This paper further investigates the ranking of OSs and their tuples as to facilitate (1) the top-k ranking
multilingual information where backend will be English database and front-end uses local languages like Hindi, Marathi or Gujrathi. Our system provides an interface to enter a keyword in local language, the keyword will be parsed, query will be formed and display the result in local language. We had developed an efficient
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.