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The World Wide Web has become ubiquitous. Heterogeneity of the Web space consists in web pages conceptuality, content of documents and variety of the files. This heterogeneity is becoming a challenge in the information retrieval, information integration, information exploring and mining of the web. The main idea of this paper is to create a novel approach for the modelling of the Web space by an algebraic mechanism which models the heterogeneous Web warehouse. The need for computational efficiency is well-recognized by the data mining community, which sprung from the database community concern for efficient manipulation of large datasets. We present our initial development of an algebraic model named WDHAS for gathering, analyzing, and redeploying web data. Not dissimilar to conventional data mining, the general idea is that good use of web data first requires the careful selection of data (both usage and content data), the deployment of appropriate learning methods, and the evaluation of the results of applying the results of learning in a web application. Our algebraic model includes a framework which can deal with tools for building, using, and visualizing web abstractions. This paper is organized as follows. In the first section we get the arguments for algebraic modelling. Section 2 presents details of the WDHAS model. Section 3 emphases the properties of the WDHAS hierarchy base. Section 4 presents an application of the model to Hypertext Abstract Machine, showing different pattern-making like abstract objects and their operations.