Abstract. We consider the problem of evaluating a large number of XPath expressions on an XML stream. Our main contribution consists in showing that Deterministic Finite Automata (DFA) can be used effectively for this problem: in our experiments we achieve a throughput of about 5.4MB/s, independent of the number of XPath expressions (up to 1,000,000 in our tests). The major problem we face is that of the size of the DFA. Since the number of states grows exponentially with the number of XPath expressions, it was previously believed that DFAs cannot be used to process large sets of expressions. We make a theoretical analysis of the number of states in the DFA resulting from XPath expressions, and consider both the case when it is constructed eagerly, and when it is constructed lazily. Our analysis indicates that, when the automaton is constructed lazily, and under certain assumptions about the structure of the input XML data, the number of states in the lazy DFA is manageable. We also validate experimentally our findings, on both synthetic and real XML data sets. 1

Keyword search is a proven, user-friendly way to query HTML documents in the World Wide Web. We propose keyword search in XML documents, modeled as labeled trees, and describe corresponding efficient algorithms. The proposed keyword search returns

We identify crucial design issues in building a distributed inverted index for a large collection of Web pages. We introduce a novel pipelining technique for structuring the core index-building system that substantially reduces the index construction time. We also propose a storage scheme for creating and managing inverted files using an embedded database system. We suggest and compare different strategies for collecting global statistics from distributed inverted indexes. Finally, we present performance results from experiments on a testbed distributed Web indexing system that we have implemented.

We present WSQ/DSQ (pronounced "wisk-disk"), a new approach for combining the query facilities of traditional databases with existing search engines on the Web. WSQ, for Web-Supported (Database) Queries, leverages results from Web searches to enhance SQL queries over a relational database. DSQ, for Database-Supported (Web) Queries, uses information stored in the database to enhance and explain Web searches. This paper focuses primarily on WSQ, describing a simple, low-overhead way to support WSQ in a relational DBMS, and demonstrating the utility of WSQ with a number of interesting queries and results. The queries supported by WSQ are enabled by two virtual tables, whose tuples represent Web search results generated dynamically during query execution. WSQ query execution may involve many high-latency calls to one or more search engines, during which the query processor is idle. We present a lightweight technique called asynchronous iteration that can be integrated easily into a standard sequential query processor to enable concurrency between query processing and multiple Web search requests. Asynchronous iteration has broader applications than WSQ alone, and it opens up many interesting query optimization issues. We have developed a prototype implementation of WSQ by extending a DBMS with virtual tables and asynchronous iteration; performance results are reported. 1

AbstractÐIn this paper, we present a clustering and indexing paradigm (called Clindex) for high-dimensional search spaces. The scheme is designed for approximate similarity searches, where one would like to find many of the data points near a target point, but where one can tolerate missing a few near points. For such searches, our scheme can find near points with high recall in very few IOs and perform significantly better than other approaches. Our scheme is based on finding clusters and, then, building a simple but efficient index for them. We analyze the trade-offs involved in clustering and building such an index structure, and present extensive experimental results. Index TermsÐApproximate search, clustering, high-dimensional index, similarity search. 1

The MIX mediator systems incorporates a novel framework for navigation-driven evaluation of virtual mediated views. Its architecture allows the on-demand computation of views and query results as the user navigates them. The evaluation scheme minimizes superfluous source access through the use of lazy mediators that translate incoming client navigations on virtual XML views into navigations on lower level mediators or wrapped sources. The proposed demand-driven approach is inevitable for handling up-to-date mediated views of large Web sources or query results. The non-materialization of the query answer is transparent to the client application since clients can navigate the query answer using a subset of the standard DOM API for XML documents. We elaborate on query evaluation in such a framework and show how algebraic plans can be implemented as trees of lazy mediators. Finally, we present a new buffering technique that can mediate between the fine granularity of DOM navigations and the coarse granularity of real world sources. This drastically reduces communication overhead and also simplifies wrapper development. An implementation of the system is available on the Web.

Extended version An Archival Repository reliably stores digital objects for long periods of time (decades or centuries). The archival nature of the system requires new techniques for storing, indexing, and replicating digital objects. In this paper we discuss the specialized indexing needs of a write-once archive. We also present a reliability algorithm for effectively replicating sets of related objects. We describe an administrative user interface and a data import utility for archival repositories. Finally, we discuss and evaluate a prototype repository we have built, the Stanford Archival Vault, SAV.

We study the problem of generating efficient, equivalent rewritings using views to compute the answer to a query. We take the closed-world assumption, in which views are materialized from base relations, rather than views describing sources in terms of abstract predicates, as is common when the open-world assumption is used. In the closedworld model, there can be an infinite number of different rewritings that compute the same answer, yet have quite different performance. Query optimizers take a logical plan (a rewriting of the query) as an input, and generate efficient physical plans to compute the answer. Thus our goal is to generate a small subset of the possible logical plans without missing an optimal physical plan.

Abstract Miniaturization of computing devices, and advances in wireless communication and sensor technology are some of the forces that are propagating computing from the stationary desktop to the mobile outdoors. Some important classes of new applications that will be enabled by this revolutionary development include location-based services, tourist services, mobile electronic commerce, and digital battlefield. Some existing application classes that will benefit from the development include transportation and air traffic control, weather forecasting, emergency response, mobile resource management, and mobile workforce. Location management, i.e. the management of transient location information, is an enabling technology for all these applications. Location management is also a fundamental component of other technologies such as fly-through visualization, context awareness, augmented reality, cellular communication, and dynamic resource discovery. In this paper we present our view of the important research issues in location management. These include modeling of location information, uncertainty management, spatio-temporal data access languages, indexing and scalability issues, data mining (including traffic and location prediction), location dissemination, privacy and security, location fusion and synchronization. 1.

Despite the surge of research in continuous stream processing, there is still a semantical gap. In many cases, continuous queries are formulated in an enriched SQL-like query language without specifying the semantics of such a query precisely enough. To overcome this problem, we present a sound and precisely defined temporal operator algebra over data streams ensuring deterministic query results of continuous queries. In analogy to traditional database systems, we distinguish between a logical and physical operator algebra. While our logical operator algebra specifies the semantics of each operation in a descriptive way over temporal multisets, the physical operator algebra provides adequate implementations in form of stream-to-stream operators. We show that query plans built with either the logical or the physical algebra produce snapshot-equivalent results. Moreover, we introduce a rich set of transformation rules that forms a solid foundation for query optimization, one of the major research topics in the stream community. Examples throughout the paper motivate the applicability of our approach and illustrate the steps from query formulation to query execution.