Abstract: A method and apparatus for efficient query expansion using reduced size indices and for progressive query processing. Queries are expanded conceptually, using semantically similar and syntactically related words to those specified by the user in the query to reduce the chances of missing relevant documents. The notion of a multi-granularity information and processing structure is used to support efficient query expansion, which involves an indexing phase, a query processing and a ranking phase. In the indexing phase, semantically similar words are grouped into a concept which results in a substantial index size reduction due to the coarser granularity of semantic concepts. During query processing, the words in a query are mapped into their corresponding semantic concepts and syntactic extensions, resulting in a logical expansion of the original query. Additionally, the processing overhead is avoided. The initial query words can then be used to rank the documents in the answer set on the basis of exact, semantic and syntactic matches and also to perform progressive query processing.

Abstract: In this paper, we present a natural language interface architecture, which is used for accessing FAQ knowledge bases. Since one of the main obstacles to the efficient use of natural language interfaces is the high amount of required manual knowledge engineering, we provide an adaptive architecture to automate the acquisition of linguistic knowledge. We apply a machine learning module based on an eXtended Semantic Enumeration (XSE) tree to activate linguistic tests from semantic, syntactic, and pragmatic analyses during the traversal of the tree. The XSE-tree is built automatically based on past questions without the need for any additional linguistic knowledge.

Abstract: Granularity is an integral feature of temporal data. For instance, a person's age is commonly given to the granularity of years and the time of their next airline flight to the granularity of minutes. A granularity creates a discrete image, in terms of granules, of a (possibly continuous) time-line. We present a formal model for granularity in temporal operations that is integrated with temporal indeterminacy, or "don't know when" information. We also minimally extend the syntax and semantics of SQL-92 to support mixed granularities. This support rests on two operations, scale and cast, that move times between granularities, e.g., from days to months. We demonstrate that our solution is practical by showing how granularities can be specified in a modular fashion, and by outlining a time- and space-efficient implementation. The implementation uses several optimization strategies to mitigate the expense of accommodating multiple granularities.

Abstract: A shared information system is expected to comply with the following potentially conflicting requirements. It should provide useful answers to arbitrary queries, while on the other hand it should preserve certain secrets according to a security policy. We study and compare two previously suggested approaches to meet these requirements, namely refusal of statements and lying . The investigation is performed using a highly abstract and general framework, both with respect to the information system and the preservation of secrets. We focus on the case that the user supposedly does not know the secrecies, i.e., the alternatives consisting of an actual secret and its negation. The assessment shows that for unknown secrecies refusal is better than lying. In particular, while preserving the same secrets refusal can provide more useful answers.

Abstract: In order to exploit knowledge embedded in databases and to migrate from data to knowledge management environments, conceptual modeling languages must offer more expressiveness than traditional modeling languages. This paper proposes the conceptual graph formalism as such a modeling language. It shows through an example and a comparison with Telos, a semantically rich knowledge modeling language, that it is suited for that purpose. The conceptual graph formalism offers simplicity of use through its graphical components and small set of constructs and operators. It allows easy migration from database to knowledge base environments. Thus, this paper advocates its use.

Abstract: Data in the warehouse can be seen as materialized views generated from the underlying multiple data sources. Materialized views are used to speedup query processing on large amounts of data. These views need to be maintained in response to updates in the source data. This is often done using incremental techniques that access data from underlying sources. In the data warehousing scenario, accessing base relations can be difficult, sometimes data sources may be unavailable, since these relations are distributed across different sources. For these reasons, the issue of self-maintainability of the view is an important issue in data warehousing. In this paper we show that the warehouse views can be made self-maintainable if some additional relations, called auxiliary relations, derived from the intermediate results of the view computation can be materialized in the warehouse. We give an algorithm for determining what auxiliary relations need to be materialized in order to make a materialized view self-maintainable. We then propose an efficient self-maintainable incremental algorithm that computes the updates to both the materialized view and the additional relations. The primary objective is to minimize the overall maintenance cost of a given view and the auxiliary relations. One important feature of our algorithm is that it derives the `exact change' to every materialized additional relation, including the materialized view, without accessing the view itself. This feature is important to ensure the correctness of the update to views defined by aggregate functions, and also important in active database applications where triggers are fired by updates to the view. Finally, we compare the maintenance cost of our incremental algorithm to that of counting algorithm and recomputing the view from scratch (naive algorithm).

Abstract: S YN D I KAT E is a family of natural language understanding systems for automatically acquiring knowledge from real-world texts (e.g., information technology test reports, medical finding reports), and for transferring their content to formal representation structures which constitute a corresponding text knowledge base. We present a general system architecture which integrates requirements from the analysis of single sentences, as well as those of referentially linked sentences forming cohesive texts. Properly accounting for text cohesion phenomena is a prerequisite for the soundness and validity of the generated text representation structures. It is also crucial for any information system application making use of automatically generated text knowledge bases in a reliable way, e.g., by inferentially supported fact retrieval.

Abstract: Enterprise modelling technology prescribes systematic use and computer-aided documentation of knowledge about enterprises. The basis of this technology is the enterprise model, assumed to be developed during the organisational analysis, re-engineering or requirements acquisition processes where it serves as an additional source of knowledge elicitation as well. Enterprise modelling technology is also potentially applicable in the area of organisational learning. The enterprise model usually consists of several sub-models that have user-oriented meta-knowledge structures for communication with human sources of information. The success of the methodology in different areas depends on its representative and explanatory capabilities. Theoretical examination of the explanatory capability of enterprise models from the points of view of Aristotle’s explanatory principles shows that explanatory capability of the models usually is limited. The situation can be improved by richer representations of human-related issues in the enterprise modelling frameworks.

Abstract: The objective of this introductory paper is twofold. On one hand, it shows the guest editors's view about the complex field of Conceptual Modelling. To do that, we discuss some concepts related to this topic, as well as the relation that nowadays exists between this process and the other parts of software development. On the other hand, this introductory paper describes the papers that are included in this special issue, connecting each of these papers with the view that the guest editors have about the field.

Abstract: We present a flexible framework that enables workflow systems to adapt to changing conditions. The model is designed to reveal key aspects of the tasks involved in representing and enacting business processes. These fundamental characteristics are identified as state, behaviour, distribution, coordination and enactment. By isolating such core concepts in a way that allows them to be varied, we open up the general process of task coordination and execution, allowing for extensions in a planned way. By suitable manipulation of each of these aspects, at the appropriate level, a workflow system may be extensively modified in a way that minimises the effect of such change upon other aspects of the system.

Abstract: A range query applies an aggregation operation (e.g., SUM) over all selected cells of an OLAP data cube where the selection is specified by providing ranges of values for numeric dimensions. Range sum queries on data cubes are a powerful analysis tool. Many application domains require that data cubes are updated often and the information provided by analysis tools are current or ‘‘near current’’. Existing techniques for range sum queries on data cubes, however, can incur update costs in the order of the size of the data cube. Since the size of a data cube is exponential in the number of its dimensions, rebuilding the entire data cube can be very costly and is not realistic. To cope with this dynamic data cube problem, a new approach has been introduced recently, which achieves constant time per range sum query while constraining each update cost within OOn d=2 U, where d is the number of dimensions of the data cube and n is the number of distinct values of the domain at each dimension. In this paper, we provide a new algorithm for the problem which requires OOn 1=3 U time for each range sum query and OOn d=3 U time for each update. Our algorithm improves the update time by a factor of OOn d=6 U in contrast to the current one for the problem OOn d=2 U. Like all existing techniques, our approach to answering range sum queries is also based on some precomputed auxiliary information (prefix sums) that is used to answer ad hoc queries at run time. Under both the product model and a new model introduced in this paper, the total cost for updates and range queries of the proposed algorithm is smallest compared with the cost by all known algorithms. Therefore our algorithm reduces the overall time complexity for range sum queries significantly. ” 2000 Elsevier Science B.V. All rights reserved.

Abstract: This paper presents two techniques to integrate and abstract database schemes. The techniques assume the existence of a collection of interscheme properties describing semantic relationships holding among input database scheme objects. The former technique uses interscheme properties to produce an integrated scheme encoding a global, unified view of the whole semantics represented within input schemes. The latter one takes a (integrated) scheme as the input and yields in output an abstracted scheme encoding the same semantics as the input scheme, but represented at an higher, application-dependent abstraction level. In addition, the paper illustrates a possible application of these algorithms to the construction of a data repository. Finally, the paper presents the application of proposed techniques to some database schemes of Italian Central Governmental Offices.

Abstract: Usually, the development of an information system (or some part of it) starts with requirement elicitation followed by a phase of collecting and analyzing which results in a set of requirements specifications. As opposed to conventional conceptual modeling, where input texts are formalized, our approach suggests the idea of collecting and cataloguing natural language patterns in a non-textual form immediately after a linguistic analysis. This linguistic analysis is done according to the NTMS model. Collecting and cataloguing of natural language data is supported by KCPM.

Abstract: In content-based image retrieval systems, the content of an image such as color, shapes and textures are used to retrieve images that are similar to a query image. Most of the existing work focus on the retrieval effectiveness of using content for retrieval, i.e., study the accuracy (in terms of recall and precision) of using different representations of content. In this paper, we address the issue of retrieval efficiency, i.e., study the speed of retrieval, since a slow system is not useful for large image databases. In particular, we look at using the shape feature as the content of an image, and employ the centroid–radii model to represent the shape feature of objects in an image. This facilitates multi-resolution and similarity retrievals. Furthermore, using the model, the shape of an object can be transformed into a point in a high-dimensional data space. We can thus employ any existing high-dimensional point index as an index to speed up the retrieval of images. We propose a multi-level R-tree index, called the Nested R-trees (NR-trees) and compare its performance with that of the R-tree. Our experimental study shows that NR-trees can reduce the retrieval time significantly compared to R-tree, and facilitate similarity retrieval. We note that our NR-trees can also be used to index high-dimensional point data commonly found in many other applications.

Abstract: Information services, such as regional or tourist information services, are currently developed everywhere. Whenever a site gets very large, providers understand the need for a systematic development. Site development is similar to database co-design, which includes structures, functionality, and interfaces. Additionally, interfaces are even more important for sites and need a very sophisticated support whenever the site is raising to large sites. Metaphorical structures, i.e., metaphors, allegories, metonymies or synecdoches, can be used to help the scanning user understand a page. In general, metaphorical structures have a communicative or cognitive function. For example, many users do not realize that within a computer context a trash can often stand as a metaphor for the action of deleting files. The users can understand content, functionality, and intention intuitively via using such metaphorical structures. Site development can profit from well-integrated metaphorical structures aimed at focus on a deeper context explanation as well as on a more specific navigation and selection. Metaphorical structures for sites can be developed based on linguistic and cognitive research. Stand-alone metaphors have often been used for sites. The power of metaphorical structures can be best exploited if they are used for complex actions and in an integrated way together with structure, functionality, and interfaces. This paper shows how the co-design approach allows for the consistent development of metaphorical structures in an integrated manner.

Abstract: When software engineers set out to build a system, they usually have the informal idea that there is a relation between the linguistic world and the conceptual world. In this paper, we present a formalisation of this empirical relation, defining an intermediate mapping of the components of the linguistic and conceptual worlds to their mathematical representations. This process outputs a justified correspondence between natural language, used as a means of communication between users and software engineers, and conceptual models, employed by software engineers as a first step towards building a system. In other words, our aim is to show how the equivalence of the linguistic and conceptual representations of a requirement can be established in a formal and justified manner.

Abstract: Large information bases that are used by several different users and applications accommodate the demands of their users more effectively, if they can be split into possibly overlapping fragments, called contexts. The latter allow one to focus attention on specific concerns such as topics, tasks, or user-views. This paper proposes a conceptual, generic framework for contexts supporting context-specific naming and representation of conceptual entities, relativized transaction execution, operations for context construction and manipulation, authorization, and change propagation. A partial validation of the framework is given by showing how specific topologies of contexts, associated with specific authorization and change propagation policies, result in design templates for modeling well-known applications such as modules, views and workspaces. Further, examples are used to illustrate how modifications of the templates lead to generalizations of these applications that better support specific applications, such as those calling for tight cooperative work. The context framework is aimed at providing a common kernel for the modeling of information base partitions in general and well-known notions such as views, workspaces, topics, versions and requirements engineering viewpoints, in particular.

Abstract: Content-based image retrieval plays an important role in many multimedia applications. Images are typically retrieved based on a given sample image, a sketch or a simple description of the content. The rate of this retrieval is undeniably gaining importance as databases increase constantly in size. In this paper, we present MOSAIC, an image retrieval system that we have developed. In MOSAIC, an image is represented by a set of clusters , each of which captures information on multiple features – the “color” of the cluster, the “size” of the cluster and the “spatial” location of the cluster. We also propose an index structure, to facilitate speedy retrieval of images. The structure is multi-tier with each tier dealing with one feature. In this way, images that are dissimilar in the higher tier can be pruned away immediately. We implemented and evaluated MOSAIC, and our results show that the system can retrieve relevant images effectively and efficiently.

Abstract: Structured text is a general concept that is implicit in a variety of approaches to handling information. Syntactically, an item of structured text is a number of grammatically simple phrases together with a semantic label for each phrase. Items of structured text may be nested within larger items of structured text. The semantic labels in a structured text are meant to parameterize a stereotypical situation, and so a particular item of structured text is an instance of that stereotypical situation. Much information is potentially available as structured text including tagged text in XML, text in relational and object-oriented databases, and the output from information extraction systems in the form of instantiated templates. In this paper, we formalize the concept of structured text, and then focus on how we can identify inconsistency in the logical representation of items of structured text. We then present a new framework for merging logical theories that can be employed to merge inconsistent items of structured text. To illustrate, we consider the problem of merging reports such as weather reports.

Abstract: This paper introduces a general, set-theoretic model for expressing dynamic integrity constraints, i.e., integrity constraints on the state changes that are allowed in a given state space. In a managerial context, such dynamic integrity constraints can be seen as representations of "real world" constraints and business rules. This topic has important practical applications in many business areas. The notions of (direct) transition, reversible and irreversible transition, transition relation, and consistency of a transition relation will be introduced. The expected link with Kripke models (for modal and temporal logics) is also made explicit. Several practical examples of dynamic integrity constraints will illustrate the applicability of the theory. Some important subclasses of dynamic integrity constraints in a database context will be identified, e.g., various forms of cumulativity (which can be regarded as "transitional" inclusion dependencies concerning two different "points in time"), non-decreasing values, integrity constraints on initial and final values, life cycles, changing life cycles, and transition and constant dependencies. Several formal properties of these dependencies will be derived. For instance, it turns out that functional dependencies can be considered as "degenerated" transition dependencies. Also, the distinction between primary keys and alternate keys is reexamined; from a dynamic point of view. (C) 2000 Elsevier Science B.V. All rights reserved.

Abstract: The notion of giving support to composite objects in systems is gaining strength in a number of areas. In this paper we examine the usefulness of introducing part-of reasoning in a description logic in a document management environment. We identify key issues in both expressivity and inferencing. We define a language that allows for differentiating between different kinds of parts and definition of domains, number restrictions and ordering of parts. We identified also questions and inferences which are useful in document management. This has led us to define a part-of hierarchy for individuals and inferences concerning the assembly of composite objects.

Abstract: In the performance of activities in an organization, communication plays a dominant role in that it allows people to coordinate their activities. They organize their activities by having conversations intending to initiate actions and report on them. The modeling of business communication is a central part in the communication-centered organizational modeling approach called dynamic essential modeling of organizations (DEMO), and is important for specifying the behavior of participating actors in detail. According to DEMO, by performing communicative acts, we call them organization primitives, different kinds of commitments are produced and mutual obligations are established. In this paper, we elaborate on the profits of using linguistic instruments for modeling business communication. In particular, we examine how functional grammar (FG) can be used to determine the (structure of) organization primitives. To illustrate this we use some expressions extracted from an actual conversation involving a hotel reservation. In addition, we focus on the profits of using FG for requirements engineering by an exploration of the relation between FG and Conceptual Prototyping Language (CPL). For this examination, we use a requirements document concerning the reservation function of a hotel.

Abstract: Modern database systems and storage manager toolkits usually provide a large object abstraction. Very often large objects are not used as standalone entities, but rather embedded within an aggregate of different types, i.e. a tuple . Depending on the large object's size and access probability, query performance is determined by the representation of the large object: either inlined within the aggregate or swapped out to a separate object. This paper describes a sound and general large object interface extension which automatically switches the representation of large objects according to their actual size. The optimum threshold size for switching the large object's representation is determined, based upon a linear cost model. Furthermore, a SHORE-based implementation and its performance are presented. It turns out that switching the representation of large objects yields great performance improvements for objects whose size is varying from quite small to large.

Abstract: The design of an information system (IS) has many consequences for the work of its users. We describe a methodical structure that applies conceptual modeling for the iterative, coordinated design of user work and its supporting IS software. Our goal for this structure is to support an effective, efficient dialog between domain experts and computing technologists. However, the design of work and the design of software require different modeling languages, so we describe the requirements for conceptual modeling of work versus the software needed to support it. We also describe some techniques for relating the two types of models to support iterative design on two converging tracks, one for work and the other for its supporting software.

Abstract: Most of all index structures based on the R-tree have failed to support eAcient indexing mechanisms for similarity search in high-dimensional data spaces. This is due to the fact that most of the index structures commonly use balanced split strategy in order to guarantee storage utilization and the shape of queries for similarity search is a hypersphere in high-dimensional spaces. In this paper, we propose the Spherical Pyramid-Technique (SPY-TEC), an eAcient indexing method for similarity search in high-dimensional data space. The SPY-TEC is based on a special partitioning strategy, which is to divide the d-dimensional data space first into 2d spherical pyramids, and then cut the single spherical pyramid into several spherical slices. This partition provides a transformation of d-dimensional space into one-dimensional space as the Pyramid-Technique [14] does. Thus, we are able to use a B a -tree to manage the transformed one-dimensional data. We also propose the algorithms to process hyperspherical range queries on the data space partitioned by this partitioning strategy. Finally, we show that the SPY-TEC clearly outperforms other related techniques including the Pyramid-Technique in processing hyperspherical range queries through various experiments using synthetic and real data. ” 2000 Elsevier Science B.V. All rights reserved.

Abstract: This paper contributes a method for developing interactive multimedia in a multimedia information system through the modelling of their semantic content. The use of the method is demonstrated with the development of an interactive instructional multimedia information system.

Abstract: The tremendous growth in size, complexity and value of the organization’s data resources has given rise to an urgent need for a data integrity standard that will provide a consensus definition, a common measure and a set of tools for evaluating the various models and mechanisms in this domain. This paper attempts to pave the way for such a data integrity standard. It discusses various definitions of data integrity and indicates the one that best serves as a common definition. It then provides a description and assessment of two prominent data integrity models: the Biba model, and the Clark–Wilson model. Next, a framework for evaluating these models is proposed and operationalized. The final section discusses conclusions and makes some practical recommendations that derive from the comparison of the models.

Abstract: Generalized queries are defined as sets of clauses in implication form. They cover several tasks of practical importance for database maintenance such as answering positive queries, computing database completions and integrity constraints checking. We address the issue of answering generalized queries under the minimal model semantics for the class of disjunctive deductive databases (DDDBs). The advanced approach is based on having the query induce an order on the models returned by a sound and complete minimal model generating procedure. We consider answers that are true in all and those that are true in some minimal models of the theory. We address the issue of answering positive queries through the construction of the minimal model state of the DDDB, using a minimal model generating procedure. The refinements allowed by the procedure include isolating a minimal component of a disjunctive answer, the specification of possible updates to the theory to enable the derivability of certain queries and deciding the monotonicity properties of answers to different classes of queries.

Abstract: Classification query language (CQL) is a high-level visual query language with a great expressive power. In CQL the processing of ordinary relations and classifications based on transitive relationships is integrated seamlessly. Relations and classifications are represented in the visual interface in a uniform way through relation and classification skeletons. All query formulation in CQL is QBE-like – based on the intuitive way of filling constants and sample values into the skeletons. In order to guarantee great expressive power, relational and classification expressions can be nested freely with each other at unlimited nesting levels. Recursive definition of transitive processing is totally hidden from the users. The query interface and its implementation are described briefly.