Frequent sequence mining is one of the fundamental building blocks in data mining. While the problem has been extensively studied, few of the available techniques are sufficiently scalable to handle datasets with billions of sequences; such large-scale datasets arise, for instance, in text mining and session analysis. In this paper, we propose MG-FSM, a scalable algorithm for frequent sequence mining on MapReduce. MG-FSM can handle so-called "gap constraints", which can be used to limit the output to a controlled set of frequent sequences. At its heart, MG-FSM partitions the input database in a way that allows us to mine each partition independently using any existing frequent sequence mining algorithm. We introduce the notion of w-equivalency, which is a generalization of the notion of a "projected database" used by many frequent pattern mining algorithms. We also present a number of optimization techniques that minimize partition size, and therefore computational and communication costs, while still maintaining correctness. Our experimental study in the context of text mining suggests that MG-FSM is significantly more efficient and scalable than alternative approaches.

We consider the problem of rewriting XQuery queries using multiple materialized XQuery views. The XQuery dialect we use to express views and queries corresponds to tree patterns (returning data from several nodes, at different granularities, ranging from node identifiers to full XML subtrees) with value joins. We provide correct and complete algorithms for finding minimal rewritings, in which no view is redundant. Our work extends the state of the art by considering more flexible views than the mostly XPath 1.0 dialects previously considered, and more powerful rewritings. We implemented our algorithms and assess their performance through a set of experiments.

The proliferation of electronic content has notably lead to the apparition of large corpora of interrelated structured documents (such as HTML and XML Web pages) and semantic annotations (typically expressed in RDF), which further complement these documents. Documents and annotations may be authored independently by different users or programs. We present AnnoVIP, a peer-to-peer platform, capable of efficiently exploiting a multitude of annotated documents, based on innovative materialized views.

Mash-ups are being used in various Web-based applications of Web 2.0 which combine instantly information from different sources. Active XML (AXML, in short) language is a tool for decentralized, data-centric Web service integration. AXML document includes calls to services that may be either simple request-responses either long running subscriptions. Being fully composable and allowing resource sharing makes AXML ideal for mash-up style integration. In this demo we present how AXML can be used as a specification, optimization and distributed execution language for dynamic distributed mash-ups in varied P2P settings. We also demonstrate our AXML optimizer's (OptimAX) optimization rules and rewriting engine with a help of GUI.

The Web has become a platform of choice for the deployment of complex applications involving several business partners. Typically, such applications interoperate by means of Web services, exchanging XML information. We present OptimAX, an optimization Web service that applies at the static level (prior to enacting an application) in order to rewrite it into one whose execution will be more performant. OptimAX builds on the ActiveXML (AXML) data-centric Web service composition language, and demonstrates how database-style techniques can be efficiently integrated in a loosely-coupled, distributed application based on Web services. OptimAX has been fully implemented and we describe its experimental performance.

We present the WebContent platform for managing distributed repositories of XML and semantic Web data. The platform allows integrating various data processing building blocks (crawling, translation, semantic annotation, full-text search, structured XML querying, and semantic querying), presented as Web services, into a large-scale efficient platform. Calls to various services are combined inside ActiveXML [8] documents, which are XML documents including service calls. An ActiveXML optimizer is used to: ( i ) efficiently distribute computations among sites; ( ii ) perform XQuery-specific optimizations by leveraging an algebraic XQuery optimizer; and ( iii ) given an XML query, chose among several distributed indices the most appropriate in order to answer the query.