R. Krishnamurthy and T. Imielinksi. Practitioner problems in need of database research: Research directions in knowledge discovery. ACM SIGMOD RECORD, 20(3):76-78, sept 1991.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....research in the database community, the classi cation problem is re examined in the context of large databases. Unlike the researchers in other elds, database researchers pay more attention to the issues related to the volume of data and are concerned with the eciency of data retrieval mechanisms [6]. Two major approaches which attracted the attention of researchers are neural networks and decision trees. Decision tree classi ers are relatively fast compared to other classi cation methods. They can be translated into simple and easy to understand classi cation rules, even by endusers. This ....

R. Krishnamurthy and T. Imielinksi. Practitioner problems in need of database research: Research directions in knowledge discovery. ACM SIGMOD RECORD, 20(3):76-78, sept 1991.

....work on quantifying the usefulness or interestingness of a rule [PS91a] What is useful or interesting is often application dependent. The need for a human in the loop and providing tools to allowhuman guidance of the rule discovery process has been articulated, for example, in [B 93] KI91] Tsu90] We do not discuss these issues in this paper, except to point out that these are necessary features of a rule discovery system that may use our algorithms as the engine of the discovery process. 1.1 Problem Decomposition and Paper Organization The problem of discovering all ....

Ravi Krishnamurthy and Tomasz Imielinski. Practitioner problems in need of database research: Research directions in knowledge discovery. SIGMOD RECORD, 20(3):76-- 78, September 1991.

....work on quantifying the usefulness or interestingness of a rule [PS91a] What is useful or interesting is often application dependent. The need for a human in the loop and providing tools to allow human guidance of the rule discovery process has been articulated, for example, in [B 93] KI91] Tsu90] We do not discuss these issues in this paper, except to point out that these are necessary features of a rule discovery system that may use our algorithms as the engine of the discovery process. 1.1 Problem Decomposition and Paper Organization The problem of discovering all ....

Ravi Krishnamurthy and Tomasz Imielinski. Practitioner problems in need of database research: Research directions in knowledge discovery. SIGMOD RECORD, 20(3):76-- 78, September 1991.

....has been work on quantifying the usefulness or interestingness of a rule [20] What is useful or interesting is often application dependent. The need for a human in the loop and providing tools to allow human guidance of the rule discovery process has been articulated, for example, in [7] [14]. We do not discuss these issues in this paper, except to point out that these are necessary features of a rule discovery system that may use our algorithms as the engine of the discovery process. 1.1 Problem Decomposition and Paper Organization The problem of discovering all association rules ....

R. Krishnamurthy and T. Imielinski. Practitioner problems in need of database research: Research directions in knowledge discovery. SIGMOD RECORD, 20(3):76--78, September 1991.

....has been used with great success in traditional business data processing. There is an increasing desire to use this technology in new application domains. One such application domain that is likely to acquire considerable significance in the near future is database mining [12] 3] 5] 8] [9] [11] 15] 16] 18] 19] An increasing number of organizations are creating ultra large data bases (measured in gigabytes and even terabytes) of business data, such as consumer data, transaction histories, sales records, etc. Such data forms a potential gold mine of valuable business ....

....massive data. We describe a model and some basic operations for the process of rule discovery. We also show how these database mining problems map to this model and how they can be solved by using the basic operations we propose. Our view of database mining complements the perspective presented in [9, 19]. Both of these papers argue for an iterative process for mining with a human in the loop. The user begins with a hypothesis and uses data to refute or confirm the hypothesis. The hypothesis is refined, depending on the response and this process continues until a satisfactory theory has been ....

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Ravi Krishnamurthy and Tomasz Imielinski, "Practitioner Problems in Need of Database Research: Research Directions in Knowledge Discovery", SIGMOD Record , Vol. 20, No. 3, Sept. 1991, 76--78.

....of commercial database products in business data processing, the market place is showing evidence of increasing desire to use database technology in new application domains. One such application domain that is likely to acquire considerable significance in the near future is database mining [4] [10] [12] 16] 18] 17] 20] Several organizations have created ultra large data bases, running into several gigabytes and more. The databases relate to various aspects of their business and are information mines that they would like to exploit to improve the quality of their decision making. One ....

Ravi Krishnamurthy and Tomasz Imielinski, "Practitioner Problems in Need of Database Research: Research Directions in Knowledge Discovery ", SIGMOD Record , Vol. 20, No. 3, Sept. 1991, 76-78.

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Krishnamurthy, R. and Imielinski, T. 1991. Practitioner problems in need of database research: Research directions in knowledge discovery. SIGMOD Record 20, 3 (September), 76--78.

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