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Due to the growing importance of the World Wide Web, archiving it has become crucial for preserving useful source of information. To maintain a web archive up-to-date, crawlers harvest the web by iteratively downloading new versions of documents. However, it is frequent that crawlers retrieve pages with unimportant changes such as advertisements which are continually updated. Hence, web archive systems waste time and space for indexing and storing useless page versions. Also, querying the archive can take more time due to the large set of useless page versions stored. Thus, an effective method is required to know accurately when and how often important changes between versions occur in order to efficiently archive web pages. Our work focuses on addressing this requirement through a new web archiving approach that detects important changes between page versions. This approach consists in archiving the visual layout structure of a web page represented by semantic blocks. This work seeks to describe the proposed approach and to examine various related issues such as using the importance of changes between versions to optimize web crawl scheduling. The major interesting research questions that we would like to address in the future are introduced.

A pattern is a model or a template used to summarize and describe the behavior (or the trend) of a data having generally some recurrent events. Patterns have received a considerable attention in recent years and were widely studied in the data mining field. Various pattern mining approaches have been proposed and used for different applications such as network monitoring, moving object tracking, financial or medical data analysis, scientific data processing, etc. In these different contexts, discovered patterns were useful to detect anomalies, to predict data behavior (or trend), or more generally, to simplify data processing or to improve system performance. However, to the best of our knowledge, patterns have never been used in the context of web archiving. Web archiving is the process of continuously collecting and preserving portions of the World Wide Web for future generations. In this paper, we show how patterns of page changes can be useful tools to efficiently archive web sites. We first define our pattern model that describes the changes of pages. Then, we present the strategy used to (i) extract the temporal evolution of page changes, to (ii) discover patterns and to (iii) exploit them to improve web archives. We choose the archive of French public TV channels France Télévisions as a case study 1 in order to validate our approach. Our experimental evaluation based on real web pages shows the utility of patterns to improve archive quality and to optimize indexing or storing.