We know that the person might be referred by his nickname and we finds the information using inte... more We know that the person might be referred by his nickname and we finds the information using internet. Extracting information from the internet not an easy task because the same name having different entity or same entity might be referred by different name like name and its nickname. So we should know the nickname to find out the information about particular entity. We know that various sites of web contain aliases of popular celebrity in various field like music, cinema, sport etc., and does not contain alias information about common man. There is one existing methods of extracting aliases through lexical pattern based retrieval tested using real-world name-alias pairs using training data related to limited domains. In this paper, we discuss what are the problem arrive while retrieving the information, and how we should correct alias extraction in Inter-disciplinary fields. Keyword : Retrieval ,semantic metadata
With the mining capabilities of the several data mining methodologies, there are several interest... more With the mining capabilities of the several data mining methodologies, there are several interesting extensions on frequent pattern mining. The discovery of sequential patterns is one of them. It has a vast array of real world applications. It is worthy of study on extending the memory indexing approach for efficient mining of generalized sequential patterns. This paper proposes a critical review of the sequential pattern mining methods.
The discovery of sequential patterns is one of the most vibrant and useful segment of modern data... more The discovery of sequential patterns is one of the most vibrant and useful segment of modern data mining. It has a vast array of real world applications. It is worthy of study on extending the memory indexing approach for efficient mining of generalized sequential patterns. This paper proposes a a new method for sequential pattern mining. In this paper the original data set is converted in to the transformed data set, by pruning the useless data in the early stage of data mining. The results have shown that this approach is resulting in saving a lot of computational time.
We know that the person might be referred by his nickname and we finds the information using inte... more We know that the person might be referred by his nickname and we finds the information using internet. Extracting information from the internet not an easy task because the same name having different entity or same entity might be referred by different name like name and its nickname. So we should know the nickname to find out the information about particular entity. We know that various sites of web contain aliases of popular celebrity in various field like music, cinema, sport etc., and does not contain alias information about common man. There is one existing methods of extracting aliases through lexical pattern based retrieval tested using real-world name-alias pairs using training data related to limited domains. In this paper, we discuss what are the problem arrive while retrieving the information, and how we should correct alias extraction in Inter-disciplinary fields. Keyword : Retrieval ,semantic metadata
With the mining capabilities of the several data mining methodologies, there are several interest... more With the mining capabilities of the several data mining methodologies, there are several interesting extensions on frequent pattern mining. The discovery of sequential patterns is one of them. It has a vast array of real world applications. It is worthy of study on extending the memory indexing approach for efficient mining of generalized sequential patterns. This paper proposes a critical review of the sequential pattern mining methods.
The discovery of sequential patterns is one of the most vibrant and useful segment of modern data... more The discovery of sequential patterns is one of the most vibrant and useful segment of modern data mining. It has a vast array of real world applications. It is worthy of study on extending the memory indexing approach for efficient mining of generalized sequential patterns. This paper proposes a a new method for sequential pattern mining. In this paper the original data set is converted in to the transformed data set, by pruning the useless data in the early stage of data mining. The results have shown that this approach is resulting in saving a lot of computational time.
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Papers by Ravi Gedam