We present the Lorel language, designed for querying semistructured data. Semistructured data is becoming more and more prevalent, e.g., in structured documents such as HTML and when performing simple integration of data from multiple sources. Traditional data models and query languages are inappropriate, since semistructured data often is irregular, some data is missing, similar concepts are represented using different types, heterogeneous sets are present, or object structure is not fully known. Lorel is a user-friendly language in the SQL/OQL style for querying such data effectively. For wide applicability, the simple object model underlying Lorel can be viewed as an extension of ODMG and the language as an extension of OQL. The main novelties of the Lorel language are: (i) extensive use of coercion to relieve the user from the strict typing of OQL, which is inappropriate for semistructured data

Lore (for Lightweight Object Repository) is a DBMS designed specifically for managing semistructured information. Implementing Lore has required rethinking all aspects of a DBMS, including storage management, indexing, query processing and optimization, and user interfaces. This paper provides an overview of these aspects of the Lore system, as well as other novel features such as dynamic structural summaries and seamless access to data from external sources.

. HySpirit is a retrieval engine for hypermedia retrieval integrating concepts from information retrieval (IR) and deductive databases. The logical view on IR models retrieval as uncertain inference, for which we use probabilistic reasoning. Since the expressiveness of classical IR models is not sufficient for hypermedia retrieval, HySpirit is based on a probabilistic version of Datalog. In hypermedia retrieval, different nodes may contain contradictory information; thus, we introduce probabilistic four-valued Datalog. In order to support fact queries as well as contentbased retrieval, HySpirit is based on an open world assumption, but allows for predicate-specific closed world assumptions. For performing efficient retrieval on large databases, our system provides access to external data. We demonstrate the application of HySpirit by giving examples for retrieval on images, structured documents and large databases. 1 Introduction Due to the advances in hardware, processing of multimed...

One of the main unsolved problems confronting Hypertext is the navigation problem, namely the problem of having to know where you are in the database graph representing the structure of a Hypertext database, and knowing how to get to some other place you are searching for in the database graph. In order to tackle this problem we introduce a formal model for Hypertext. In this model a Hypertext database consists of an information repository, which stores the contents of the database in the form of pages, and a reachability relation which is a directed graph describing the structure of the database. The notion of a trail, which is a path in the database graph describing some logical association amongst the pages in the trail, is central to our model. We define a Hypertext query language for our model based on a subset of propositional linear temporal logic, which we claim to be a natural formalism as a basis for establishing navigation semantics for Hypertext. The output of a trail query in this language is the set (which may be infinite) of all trails that satisfy the query. We show that there is a strong connection between the output of a trail query and finite automata in the sense that, given a Hypertext database and a trail query, we can construct a finite automaton representing the output of the query, which accepts a star-free regular language. We show that the construction of the finite automaton can be done in time exponential in the number of conjunctions, between the subformulae of the trail query, plus one. Given a Hypertext database and a trail query, the problem of deciding whether there exists a trail in the database that satisfies the trail query is referred to as the model checking problem. We show that, although this problem is NP-complete for differ...

In this paper, we take the logical approach to information retrieval in order to identify and describe new concepts required for performing hypermedia retrieval. For this purpose, we consider hypertext linking of nodes, hierarchical structure of documents and document type hierarchies. These concepts are described in Datalog, a horn logic without functions. Furthermore, we discuss terminological inference and propose a new approach for its application in retrieval, for which we also describe the mapping into Datalog formulas. It turns out that this logic is able to express most of the concepts, but that a higher-level language would be more appropriate for hypermedia retrieval. 1 Introduction In the logical approach to information retrieval (IR), retrieval is interpreted as inference. For a query q, the system is searching for documents d which imply the query logically, i.e. for which the logical formula q / d is true. Due to the intrinsic vagueness and imprecision of IR, a logic tha...

Introduction New applications and the expanding rate of data being stored and circulated over distributed systems and the Internet has resulted in the development of new database technologies. The need for flexibility and accuracy in data representation and manipulation is vital in Web databases [4,34]. The most important characteristic of these applications is the diversity of the data being stored and the lack of fixed and rigid structure (i.e. schema). The core problem in semistructured data is that the structure is not fully known and this leads to querying the data in a content-based fashion, as opposed to the structure-based queries over relational databases. The special features of semistructured data define a particularly interesting domain for query languages. Computations over semistructured data can easily become infinite, even when the underlying alphabet is finite. Query languages for semistructured data have been investigated in the context of algebraic pro