Using an Interest Ontology for Improved Support in Rule Mining
نویسندگان
چکیده
This paper describes the use of a concept hierarchy for improving the results of association rule mining. Given a large set of tuples with demographic information and personal interest information, association rules can be derived, that associate ages and gender with interests. However, there are two problems. Some data sets are too sparse for coming up with rules with high support. Secondly, some data sets with abstract interests do not represent the actual interests well. To overcome these problems, we are preprocessing the data tuples using an ontology of interests. Thus, interests within tuples that are very specific are replaced by more general interests retrieved from the interest ontology. This results in many more tuples at a more general level. Feeding those tuples to an association rule miner results in rules that have better support and that better represent the reality.
منابع مشابه
Optimal Rule Selection Scheme using Concept Relationship Analysis
In Data Mining, the Association rule mining is used to retrieve the recurrent item sets. Apriori algorithm is mainly used to mine association rules. In that, rule reduction is required for efficient decision-making system. Knowledge based rule reduction schemes are used to filter the interested rules. In the existing system rule validation is not provided. Quantitative attributes are not consid...
متن کاملAn Executive Approach Based On the Production of Fuzzy Ontology Using the Semantic Web Rule Language Method (SWRL)
Today, the need to deal with ambiguous information in semantic web languages is increasing. Ontology is an important part of the W3C standards for the semantic web, used to define a conceptual standard vocabulary for the exchange of data between systems, the provision of reusable databases, and the facilitation of collaboration across multiple systems. However, classical ontology is not enough ...
متن کاملA Study on Post mining of Association Rules Targeting User Interest
Association Rule Mining means discovering interesting patterns with in large databases. Association rules are used in many application areas such as market base analysis, web log analysis, protein substructures. Several post processing methods were developed to reduce the number of rules using nonredundant rules or pruning techniques such as pruning, summarizing, grouping or visualization based...
متن کاملNumeric Multi-Objective Rule Mining Using Simulated Annealing Algorithm
Abstract as a single objective one. Measures like support, confidence and other interestingness criteria which are used for evaluating a rule, can be thought of as different objectives of association rule mining problem. Support count is the number of records, which satisfies all the conditions that exist in the rule. This objective represents the accuracy of the rules extracted from the da...
متن کاملAn Improved Semantic Schema Matching Approach
Schema matching is a critical step in many applications, such as data warehouse loading, Online Analytical Process (OLAP), Data mining, semantic web [2] and schema integration. This task is defined for finding the semantic correspondences between elements of two schemas. Recently, schema matching has found considerable interest in both research and practice. In this paper, we present a new impr...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003