ACM Transactions on Internet Technology 

About: ACM Transactions on Internet Technology is an academic journal published by Association for Computing Machinery. The journal publishes majorly in the area(s): Computer science & The Internet. It has an ISSN identifier of 1533-5399. Over the lifetime, 704 publications have been published receiving 26214 citations. The journal is also known as: Transactions on Internet technology & ACM TOIT.

Principled design of the modern Web architecture

Abstract: The World Wide Web has succeeded in large part because its software architecture has been designed to meet the needs of an Internet-scale distributed hypermedia application. The modern Web architecture emphasizes scalability of component interactions, generality of interfaces, independent deployment of components, and intermediary components to reduce interaction latency, enforce security, and encapsulate legacy systems. In this article we introduce the Representational State Transfer (REST) architectural style, developed as an abstract model of the Web architecture and used to guide our redesign and definition of the Hypertext Transfer Protocol and Uniform Resource Identifiers. We describe the software engineering principles guiding REST and the interaction constraints chosen to retain those principles, contrasting them to the constraints of other architectural styles. We then compare the abstract model to the currently deployed Web architecture in order to elicit mismatches between the existing protocols and the applications they are intended to support.

Web mining for web personalization

Abstract: Web personalization is the process of customizing a Web site to the needs of specific users, taking advantage of the knowledge acquired from the analysis of the user's navigational behavior (usage data) in correlation with other information collected in the Web context, namely, structure, content, and user profile data. Due to the explosive growth of the Web, the domain of Web personalization has gained great momentum both in the research and commercial areas. In this article we present a survey of the use of Web mining for Web personalization. More specifically, we introduce the modules that comprise a Web personalization system, emphasizing the Web usage mining module. A review of the most common methods that are used as well as technical issues that occur is given, along with a brief overview of the most popular tools and applications available from software vendors. Moreover, the most important research initiatives in the Web usage mining and personalization areas are presented.

Searching the Web

Abstract: We offer an overview of current Web search engine design. After introducing a generic search engine architecture, we examine each engine component in turn. We cover crawling, local Web page storage, indexing, and the use of link analysis for boosting search performance. The most common design and implementation techniques for each of these components are presented. For this presentation we draw from the literature and from our own experimental search engine testbed. Emphasis is on introducing the fundamental concepts and the results of several performance analyses we conducted to compare different designs.

XRel : A path-based approach to storage and retrieval of XML documents using relational databases

Abstract: This article describes XRel, a novel approach for storage and retrieval of XML documents using relational databases. In this approach, an XML document is decomposed into nodes on the basis of its tree structure and stored in relational tables according to the node type, with path information from the root to each node. XRel enables us to store XML documents using a fixed relational schema without any information about DTDs and also to utilize indices such as the B 1 -tree and the R-tree supported by database management systems. Thus, XRel does not need any extension of relational databases for storing XML documents. For processing XML queries, we present an algorithm for translating a core subset of XPath expressions into SQL queries. Finally, we demonstrate the effectiveness of this approach through several experiments using actual XML documents.

Selective Markov models for predicting Web page accesses

Abstract: The problem of predicting a user's behavior on a Web site has gained importance due to the rapid growth of the World Wide Web and the need to personalize and influence a user's browsing experience. Markov models and their variations have been found to be well suited for addressing this problem. Of the different variations of Markov models, it is generally found that higher-order Markov models display high predictive accuracies on Web sessions that they can predict. However, higher-order models are also extremely complex due to their large number of states, which increases their space and run-time requirements. In this article, we present different techniques for intelligently selecting parts of different order Markov models so that the resulting model has a reduced state complexity, while maintaining a high predictive accuracy.