The Experts below are selected from a list of 72984 Experts worldwide ranked by ideXlab platform
Kazuhiro Suwa - One of the best experts on this subject based on the ideXlab platform.
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Search extension transforms Wiki into a Relational System: A case for flavonoid metabolite database
BioData Mining, 2008Co-Authors: Masanori Arita, Kazuhiro SuwaAbstract:Background In computer science, database Systems are based on the Relational model founded by Edgar Codd in 1970. On the other hand, in the area of biology the word 'database' often refers to loosely formatted, very large text files. Although such bio-databases may describe conflicts or ambiguities (e.g. a protein pair do and do not interact, or unknown parameters) in a positive sense, the flexibility of the data format sacrifices a Systematic query mechanism equivalent to the widely used SQL. Results To overcome this disadvantage, we propose embeddable string-search commands on a Wiki-based System and designed a half-formatted database. As proof of principle, a database of flavonoid with 6902 molecular structures from over 1687 plant species was implemented on MediaWiki, the background System of Wikipedia. Registered users can describe any information in an arbitrary format. Structured part is subject to text-string searches to realize Relational operations. The System was written in PHP language as the extension of MediaWiki. All modifications are open-source and publicly available. Conclusion This scheme benefits from both the free-formatted Wiki style and the concise and structured Relational-database style. MediaWiki supports multi-user environments for document management, and the cost for database maintenance is alleviated.
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search extension transforms wiki into a Relational System a case for flavonoid metabolite database
Biodata Mining, 2008Co-Authors: Masanori Arita, Kazuhiro SuwaAbstract:Background In computer science, database Systems are based on the Relational model founded by Edgar Codd in 1970. On the other hand, in the area of biology the word 'database' often refers to loosely formatted, very large text files. Although such bio-databases may describe conflicts or ambiguities (e.g. a protein pair do and do not interact, or unknown parameters) in a positive sense, the flexibility of the data format sacrifices a Systematic query mechanism equivalent to the widely used SQL.
Masanori Arita - One of the best experts on this subject based on the ideXlab platform.
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Search extension transforms Wiki into a Relational System: A case for flavonoid metabolite database
BioData Mining, 2008Co-Authors: Masanori Arita, Kazuhiro SuwaAbstract:Background In computer science, database Systems are based on the Relational model founded by Edgar Codd in 1970. On the other hand, in the area of biology the word 'database' often refers to loosely formatted, very large text files. Although such bio-databases may describe conflicts or ambiguities (e.g. a protein pair do and do not interact, or unknown parameters) in a positive sense, the flexibility of the data format sacrifices a Systematic query mechanism equivalent to the widely used SQL. Results To overcome this disadvantage, we propose embeddable string-search commands on a Wiki-based System and designed a half-formatted database. As proof of principle, a database of flavonoid with 6902 molecular structures from over 1687 plant species was implemented on MediaWiki, the background System of Wikipedia. Registered users can describe any information in an arbitrary format. Structured part is subject to text-string searches to realize Relational operations. The System was written in PHP language as the extension of MediaWiki. All modifications are open-source and publicly available. Conclusion This scheme benefits from both the free-formatted Wiki style and the concise and structured Relational-database style. MediaWiki supports multi-user environments for document management, and the cost for database maintenance is alleviated.
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search extension transforms wiki into a Relational System a case for flavonoid metabolite database
Biodata Mining, 2008Co-Authors: Masanori Arita, Kazuhiro SuwaAbstract:Background In computer science, database Systems are based on the Relational model founded by Edgar Codd in 1970. On the other hand, in the area of biology the word 'database' often refers to loosely formatted, very large text files. Although such bio-databases may describe conflicts or ambiguities (e.g. a protein pair do and do not interact, or unknown parameters) in a positive sense, the flexibility of the data format sacrifices a Systematic query mechanism equivalent to the widely used SQL.
Carlo Zaniolo - One of the best experts on this subject based on the ideXlab platform.
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ICDE - Design and implementation of a temporal extension of SQL
Proceedings 19th International Conference on Data Engineering (Cat. No.03CH37405), 2003Co-Authors: C.x. Chen, J Kong, Carlo ZanioloAbstract:We present a valid-time extension of SQL and investigate its efficient implementation on an object-Relational database System. We propose an approach, where temporal queries are expressed using a point-based time model, which only requires minimal extensions to SQL: 1999. Our prototype System called TENORS (for Temporal ENhanced Object-Relational System) maps the external point-based temporal queries and data model into equivalent internal representations based on time intervals. We describe the mapping of queries from external views to internal relations, and the temporal clustering and indexing methods used to support these queries on DB2.
M. F. N. De Boer - One of the best experts on this subject based on the ideXlab platform.
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ICDE - Query optimization strategies for browsing sessions
Proceedings of 1994 IEEE 10th International Conference on Data Engineering, 1Co-Authors: Martin L. Kersten, M. F. N. De BoerAbstract:This paper describes techniques and experimental results to obtain response time improvement for a browsing session, i.e. a sequence of interrelated queries to locate a subset of interest. The optimization technique exploits symbolic analysis of the query interdependencies and retention of (partial) query answers. A prototype browsing session optimizer (BSO) has been constructed that runs as a front-end to the Ingres Relational System. Based on the experiments reported, we propose to extend (existing) DBMSs with a mechanism to keep and reuse small answers by default. Such investments quickly pay off in sessions with interrelated queries. >
David A. Grossman - One of the best experts on this subject based on the ideXlab platform.
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integrating structured data and text a Relational approach
Journal of the Association for Information Science and Technology, 1997Co-Authors: David A. Grossman, Ophir Frieder, David O Holmes, David C RobertsAbstract:To integrate structured data and text the unchanged standard Relational model is used. Starting with the premise that a Relational System could be used to implement an Information Retrieval (IR) System, the key contribution of this thesis is a parallel approach that allows users to combine both structured and unstructured data in a single query. The hypothesis was that the Relational model would be a suitable environment for this approach, this hypothesis was verified through several prototype implementations. Additionally, a focus was on improving run-time performance without a corresponding degradation in accuracy. The hypothesis was that query terms could be reduced by using the term frequency across the document collection. This hypothesis, was verified by numerous experiments on the standard two gigabyte Tipster collection. It was consistently found that using twenty-five to thirty-three percent of the query is sufficient to obtain good performance. Maintaining accuracy in the presence of corrupted data was another focus of this work. It was found that using term fragments or n-grams provides a less than five percent degradation over corrupted data (the data was artificially ten percent corrupted) as compared with non-corrupted data. Finally, the flexibility of this approach was verified by implementing both n-grams and passage based relevance in the Relational model and using this approach for the English, Corrupted, and Spanish portions of the TIPSTER collection.
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DEXA - Structuring Text within a Relational System
Database and Expert Systems Applications, 1992Co-Authors: David A. Grossman, James R. DriscollAbstract:We introduce a preprocessor that uses a Relational System and semantic modeling to impose structure on text. Our intent is to show that document retrieval applications can be easily developed within the Relational model. We illustrate several operations that are typically found in information retrieval Systems, and show how each can be performed in the Relational model. These include keywording, proximity searches, and relevance ranking. We also include a discussion of an extension to relevance based on semantic modeling.
