Download Advances in Web Mining and Web Usage Analysis: 6th by Bamshad Mobasher, Olfa Nasraoui, Bing Liu, Brij Masand PDF

By Bamshad Mobasher, Olfa Nasraoui, Bing Liu, Brij Masand

This ebook constitutes the completely refereed post-proceedings of the sixth foreign Workshop on Mining internet info, WEBKDD 2004, held in Seattle, WA, united states in August 2004 together with the tenth ACM SIGKDD foreign convention on wisdom Discovery and information Mining, KDD 2004.

The eleven revised complete papers provided including a close preface went via rounds of reviewing and development and have been carfully chosen for inclusion within the booklet. The prolonged papers are subdivided into four basic teams: net utilization research and person modeling, internet personalization and recommender structures, seek personalization, and semantic net mining. The latter includes additionally papers from the joint KDD workshop on Mining for and from the Semantic internet, MSW 2004.

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Read or Download Advances in Web Mining and Web Usage Analysis: 6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004, Seattle, WA, USA, August 22-25, PDF

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Extra info for Advances in Web Mining and Web Usage Analysis: 6th International Workshop on Knowledge Discovery on the Web, WEBKDD 2004, Seattle, WA, USA, August 22-25,

Example text

Bn ), b ∈ D(B1 , . . , Bn ) two mappings are required: (i) the coordinate transformation t : D(A1 , . . , Am ) → D(B1 , . . ,Bn (T is actually an operator). ,Am , p be a dimension, which is to be filled during the ETL process. ,A is referred to as valid semantic basis for D). ,Ak be another semantic basis that fulfills {A1 , . . , A } ⊆ {A1 , . . , Ak }. ,A . The mapping T ◦ Π is denoted as ETL basis transformation for dimension D. Analogously, an ETL coordinate transformation t ◦ π can be defined.

This component could be replaced by any other commercial or non-commercial ROLAP engine. 2 Overall Architecture of the WUSAN System Fig. 2 on the facing page depicts the overall architecture of WUSAN. 2 on page 26), which implement a cursor and deliver data to the population component record by record. Streams also provide meta-data about their attributes – a prerequisite for subsequent ETL transformations. The population component takes each record and performs a set of data transformations (for example extracting, combining, or splitting attributes), the results of which are written to relational schemas that are modeled in an object-oriented way.

If μA ≡ ID(A) , that is the identical mapping is chosen as semantic basis, (A, ID(A) ) is described as numeric attribute. If D(A) is a countable subset of R, (A, μA ) is characterized as discrete attribute. If D(A) = {0, 1, . . , n}, n ∈ N, and μA does not stand for the identical mapping, (A, μA ) is referred to as categorical attribute. If, in addition, there exists a total order5 on μ(A), (A, μA ) is called ordinal attribute. In order to simplify notation throughout the remaining of this paper, we refer to a mining attribute (A, μA ) as attribute A, but keep always in mind, that each attribute requires a semantic basis.

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