Reinforcement learning (RL) is an important class of machine learning techniques, in which intelligent agents optimize their behavior by observing and evaluating the outcomes of their repeated interactions with their environment. A key to successfully engineering such agents is to provide them with the opportunity to engage in a large number of such interactions safely and at a low cost. This is often achieved through developing simulators of such interactions, in which the agents can be trained while also different training strategies and parameters are explored. However, specifying and implementing such simulators can be a complex endeavor requiring a systematic process for capturing and analyzing both the goals and actions of the agents and the characteristics of the target environment. We propose a framework for model-driven goal-oriented development of RL simulation environments. The framework utilizes a set of extensions to a standard goal modeling notation that allows concise modeling of a large number of ways by which an intelligent agent can interact with its environment. Through subsequent formalization, the model is used by a specially constructed simulation engine to simulate agent behavior, such that off-the-shelf RL algorithms can use it as a training environment. We present the extension of the goal modeling language and its semantics, and show how models built with it can be made executable. Further, we introduce a model development and transformation toolset to allow efficient generation and execution of simulator specifications. Through experimental studies we show how the proposed language and tool can be used for assisting the RL engineering process.

This paper contributes to the philosophical foundations of conceptual modeling by addressing a number of foundational questions such as: What is a conceptual model? Among models used in computer science, which are conceptual, and which are not? How are conceptual models different from other models used in the Sciences and Engineering? The paper takes a stance in answering these questions and, in order to do that, it draws from a broad literature in philosophy, cognitive science, Logics, as well as several areas of Computer Science (including Databases, Software Engineering, Artificial Intelligence, Information Systems Engineering, among others). After a brief history of conceptual modeling, the paper addresses the aforementioned questions by proposing a characterization of conceptual models with respect to conceptual semantics and ontological commitments. Finally, we position our work w.r.t. to a "Reference Framework for Conceptual" modeling recently proposed in the literature.

We study the problem of finding related forum posts to a post at hand. We developed a multi-segment matching technique that considers posts as a set of segments each one written with a different goal in its author mind and computes the relatedness between two posts based on the similarity of their respective segments that are intended for the same goal. The questions are how our method identifies such segments, how it figures out for what each segment is intended and how it exploits this information to rank the posts. We experimentally illustrate the effectiveness and efficiency of our segmentation method and overall approach of finding related forum posts.

We study the problem of finding related forum posts to a post at hand. In contrast to traditional approaches for finding related documents that perform content comparisons across the content of the posts as a whole, we consider each post as a set of segments, each written with a different goal in mind. We advocate that the relatedness between two posts should be based on the similarity of their respective segments that are intended for the same goal, i.e., are conveying the same intention. This means that it is possible for the same terms to weigh differently in the relatedness score depending on the intention of the segment in which they are found. We have developed a segmentation method that by monitoring a number of text features can identify the parts of a post where significant jumps occur indicating a point where a segmentation should take place. The generated segments of all the posts are clustered to form intention clusters and then similarities across the posts are calculated through similarities across segments with the same intention. We experimentally illustrate the effectiveness and efficiency of our segmentation method and our overall approach of finding related forum posts.

Human activity is almost always intentional, be it in a physical context or as part of an interaction with a computer system. By understanding why user-generated events are happening and what purposes they serve, a system can offer a significantly improved and more engaging experience. However, goals cannot be easily captured. Analyzing user actions such as clicks and purchases can reveal patterns and behaviors, but understanding the goals behind these actions is a different and challenging issue. Our work presents a unified, multidisciplinary viewpoint for goal management that covers many different cases where goals can be used and techniques with which they can be exploited. Our purpose is to provide a common reference point to the concepts and challenging tasks that need to be formally defined when someone wants to approach a data analysis problem from a goal-oriented point of view. This work also serves as a springboard to discuss several open challenges and opportunities for goal-oriented approaches in data management, analysis, and sharing systems and applications.

This tutorial provides a comprehensive and cohesive overview of goal modeling and recognition approaches by the Information Retrieval, the Artificial Intelligence and the Social Media communities. We will examine how these fields restrict the domain of study and how they capture notions easily perceived by humans' intuition but difficult to be formally defined and handled algorithmically. It is the purpose of this tutorial to provide a solid framework for placing existing work into perspective and highlight critical open challenges that will act as a springboard for researchers and practitioners in database systems, social data, and the Web, as well as developers of web-based, database-driven, and social applications, to work towards more user-centric systems and applications.

The problem of managing evolving data has attracted considerable research attention. Researchers have focused on the modeling and querying of schema/instance-level structural changes, such as, addition, deletion and modification of attributes. Databases with such a functionality are known as temporal databases. A limitation of the temporal databases is that they treat changes as independent events, while often the appearance (or elimination) of some structure in the database is the result of an evolution of some existing structure. We claim that maintaining the causal relationship between the two structures is of major importance since it allows additional reasoning to be performed and answers to be generated for queries that previously had no answers. We present here a novel framework for exploiting the evolution relationships between the structures in the database. In particular, our system combines different structures that are associated through evolution relationships into virtual structures to be used during query answering. The virtual structures define "possible" database instances, in a fashion similar to the possible worlds in the probabilistic databases. The framework includes a query answering mechanism that allows queries to be answered over these possible databases without materializing them. Evaluation of such queries raises many interesting technical challenges, since it requires the discovery of Steiner forests on the evolution graphs. On this problem we have designed and implemented a new dynamic programming algorithm with exponential complexity in the size of the input query and polynomial complexity in terms of both the attribute and the evolution data sizes.

Researchers have employed a variety of techniques to extract underlying topics that relate to software development artifacts. Typically, these techniques use semi-unsupervised machine-learning algorithms to suggest candidate word-lists. However, word-lists are difficult to interpret in the absence of meaningful summary labels. Current topic modeling techniques assume manual labelling and do not use domainspecific knowledge to improve, contextualize, or describe results for the developers. We propose a solution: automated labelled topic extraction. Topics are extracted using Latent Dirichlet Allocation (LDA) from commit-log comments recovered from source control systems such as CVS and Bit-Keeper. These topics are given labels from a generalizable cross-project taxonomy, consisting of non-functional requirements. Our approach was evaluated with experiments and case studies on two large-scale RDBMS projects: MySQL and MaxDB. The case studies show that labelled topic extraction can produce appropriate, context-sensitive labels relevant to these projects, which provides fresh insight into their evolving software development activities.

This is a demonstration of data coordination in a peer data management system through the employment of distributed triggers. The latter express in a declarative manner individual security and consistency requirements of peers, that cannot be ensured by default in the P2P environment. Peers achieve to handle in a transparent way data changes that come from local and remote actions and events. The distributed triggers are implemented as an extension of the active functionality of a centralized commercial DBMS. The language and execution semantics of distributed triggers are integrated in the kernel of the DBMS such that the latter handles transparently and simultaneously both centralized and distributed triggers. Moreover, the management of distributed triggers is associated with a set of peer acquaintance and termination protocols which are incorporated in the centralized DBMS.

In many applications it is important to find a meaningful relationship between the schemas of a source and target database. This relationship is expressed in terms of declarative logical expressions called schema mappings. The more successful previous solutions have relied on inputs such as simple element correspondences between schemas in addition to local schema constraints such as keys and referential integrity. In this paper, we investigate the use of an alternate source of information about schemas, namely the presumed presence of semantics for each table, expressed in terms of a conceptual model (CM) associated with it. Our approach first compiles each CM into a graph and represents each table's semantics as a subtree in it. We then develop algorithms for discovering subgraphs that are plausible connections between those concepts/nodes in the CM graph that have attributes participating in element correspondences. A conceptual mapping candidate is now a pair of source and target subgraphs which are semantically similar. At the end, these are converted to expressions at the database level. We offer experimental results demonstrating that, for test cases of non-trivial mapping expressions involving schemas from a number of domains, the "semantic" approach outperforms the traditional technique in terms of recall and especially precision.

We describe a mechanism based on distributed Event-Condition-Action (ECA) rules that supports data coordination in a multidatabase setting. The proposed mechanism includes an ECA rule language and a rule execution engine that transforms rules when they are first posted, and then coordinates their execution. Like traditional ECA rules, our ECA rule language has three parts: an event language, a condition language, and an action language. The event language provides a set of operators with a formal semantics for a multidatabase environment, and which allows a wide variety of composite events. The condition language provides Boolean algebra operators that take as operands either composite or simple conditions. The action language provides a conjunction of simple or composite actions. The execution model partitions rules to more easily manageable forms, distributes them to relevant databases, monitors their execution and composes their evaluations. The mechanism has been designed in a manner that minimizes the number of messages that need to be exchanged over the network. We have also conducted an experimental evaluation to compare the implementation with a naïve centralized execution model. The paper also presents a prototype implementation as well as experimental results on its performance. This work is part of an on-going project intended to develop data coordination techniques for data sharing settings.

Modern information systems often store data that has been transformed and integrated from a variety of sources. This integration may obscure the original source semantics of data items. For many tasks, it is important to be able to determine not only where data items originated, but also why they appear in the integration as they do and through what transformation they were derived. This problem is known as data provenance. In this work, we consider data provenance at the schema and mapping level. In particular, we consider how to answer questions such as "what schema elements in the source(s) contributed to this value", or "through what transformations or mappings was this value derived?" Towards this end, we elevate schemas and mappings to first-class citizens that are stored in a repository and are associated with the actual data values. An extended query language, called MXQL, is also developed that allows meta-data to be queried as regular data and we describe its implementation scenario.

We demonstrate the Toronto Mapping Adaptation System (ToMAS), a tool for automatically detecting and adapting mappings that have become invalid or inconsistent due to changes in either data semantics or schemas. Due to its modular architecture and its stand-alone nature, ToMAS can easily be applied to numerous scenarios and can interoperate with many other tools. To the best of our knowledge, no other tool can correctly maintain the consistency of the mappings under schema changes at the level of complexity supported by ToMAS.

Enterprise JavaBean (hereafter EJB) technology has been widely adopted in software industry to develop Web information systems. However, most of EJB applications are reengineered from legacy database applications. This means that legacy SQL statements need to be translated into EJB client code. Since many methods in Enterprise Beans can be regarded as view definitions of the underlying database, the EJB client code generation can be mapped to the problem of query rewriting using views. This paper addresses the automatic generation of EJB client code using query rewriting.

Task analysis has been used traditionally in HCI and CSCW to define requirements for user interfaces, Web-based or otherwise. This paper argues that a shift of paradigm is needed in Web engineering from task-oriented to goal-oriented approaches for designing applications delivering a quality user experience and achieving the objectives of the stakeholders. Task models focus on fine-grained and precisely defined user needs, thereby risking a commitment to premature design decisions. Moreover, since task analysis focuses on users doing things with the system, tasks do not capture the goals of other stakeholders who are not users. Goal-oriented methods, on the other hand, provide specific support for coping with high-level users' and stakeholders' goals, facilitates the exploration of design alternatives and the definition of requirements at a suitable level of abstraction. As such, goal-based techniques are more suitable for early stages of requirements analysis; task models can be used for later stages, such as detailed interaction design and usability evaluation. The paper conducts a detailed comparison of task and goal-analysis design techniques, using an ongoing project for a museum Web site to illustrate the two techniques and their relative strengths.

Semantic web services are web services with associated semantic descriptions. These descriptions will make it possible for other programs to select, compose and monitor web services at run-time, thereby contributing to the realization of the Semantic Web vision. Researchers have already been active in making the notion of semantic web service more concrete through usage scenaria and technologies that will support their design and use (e.g., [1]). Software Engineering has grappled with the problem of software design for more than three decades. There is welldocumented evidence that designing software manually is a laborious and error-prone task. Semantic descriptions of software (e.g., requirements and design specifications), developed and used at design-time, can facilitate the process of software construction, but they are not panacea. With semantic web services, we seem to be trying to solve the same software development problem, but now these semantic descriptions are used (for selection, composition, monitoring and other purposes) at run-time, automatically. Can we ever hope to see semantic web service technologies and methodologies that actually work? The discussion will focus on this central theme; it will be structured according to the following questions:

We explore the use of a semantic model to support a group of strategic business analysts in their daily work. In particular, we present a set of modeling constructs for representing goals, events and actors that are relevant to the work of analysts. We also describe a qualitative goal analysis procedure which makes it possible to reason about a goal model under different assumptions. The paper also reports on an incremental document classification scheme that can be used to classify relevant documents with respect to the concepts constituting the semantic model.

As Web technology spreads, the number, variety, and sophistication of Web based information services is literally exploding. While some effort has been put into managing a single, centrally controlled Web site, current Web technologies offer little help for managing Web based applications in-the-large. This is partly due to the distributed, heterogeneous, and open nature of such applications. The paper proposes a generic framework for managing Web based applications which addresses both semantic and managerial issues. Semantic issues are addressed through the inclusion of a domain model component in the framework which describes the kinds of information that are available. Management issues are treated through a framework which includes formally defined notions for an information model, information base consistency, transactions, and concurrency control. Thus, the proposed management system provides a semantically robust environment for Web based information services while allowing for Web source independence.

The large quantity and often questionable quality of available information in the information age provides a shaky foundation for decision making by individuals and organizations alike. This has created a tremendous demand for information services which can access, filter, process and present information on an as-needed basis. However, two factors complicate the design of such information services, namely the distributed and the autonomous nature of data sources. This paper reports on the design and implementation of a generic architecture for supporting information services, which meets the above challenge. The architecture adopts concepts from conceptual modeling to offer a transparent description of the information sources' setting and uses active databases techniques to offer a declarative, event-based language for defining coordination rules for integrating distributed information services. Accordingly, the proposed architecture supports two of the most prominent utilities of information services, namely the pre-designed flow of operations and the reactive provision of information. In addition to describing the architecture and illustrating its features with an example, the paper presents a prototype implementation and reports on some experimental performance results.

The World Wide Web serves as a leading vehicle for information dissemination by offering information services, such as product information, group interactions, or sales transactions. Three major factors affect the performance and reliability of information services for the Web, namely the distribution of information which has resulted from the globalization of information systems, the heterogeneity of information sources, and the sources' instability caused by autonomous evolution. This paper focuses on integrating existing information sources, available via the Web, in the delivery of information services. The primary objective of the paper is to provide mechanisms for structuring and maintaining domain models for Web applications. These mechanisms are based on conceptual modeling techniques, where concepts are being defined and refined within a metadata repository through the use of instantiation, specialization and attribution. Also, active databases techniques are exploited to provide robust mechanisms for maintaining a consistent domain model in a rapidly evolving environment, such as the Web. Therefore, the main contribution of the paper lies in the provision of an architecture for semi-automatic generation and maintenance of user-oriented, semantic-based domain models that describe distributed heterogeneous information sources.

In the late '70s, while second generation DBMS products and technologies were entering the market, there was significant research activity whose aim was to make greater use of semantic information in database systems. The focus of that research was primarily on semantic data models and data modelling, including semantic query processing and integrity checking. However, few if any of the results of these efforts found their way in database technologies of the day, or database management practices. Instead, semantic issues were delegated to early phases of information system development (including requirements analysis and design), as well as application development.

As information systems are increasingly expected to work with humans cooperatively in complex organizational contexts, conceptual modelling techniques need to be extended to relate information structures and processes to business and organizational objectives. We propose a framework which focuses on the modelling of strategic actor relationships (“A-R”) for a richer conceptual model of business processes in their organizational settings. Organizations are viewed as being made up of social actors who are intentional — have motivations, wants, and beliefs — and strategic — they evaluate their relationships to each other in terms of opportunities and vulnerabilities. The framework supports formal modelling of the network of dependency relationships among actors, and the systematic exploration and assessment of alternative process designs in reengineering. The semantics of the modelling concepts are axiomatically characterized. By embedding the framework in the Telos language, the framework can also potentially serve as an early-requirements phase tool in a comprehensive information system development environment.

Large knowledge bases that are intended for applications such as CAD, corporate repositories or process control will have to be shared by multiple users. For these systems to scale up, to give acceptable performance and to exhibit consistent behavior, it is mandatory to synchronize user transactions using a concurrency control algorithm. In this paper, we examine a novel concurrency control policy called Dynamic Directed Graph (or DDG) policy that effectively exploits the rich semantic structure of a knowledge base.

The power of any information system technology is delimited by the expressiveness of the notation used to represent information. Classification constitutes a fundamental notational structuring mechanism and, not surprisingly, is supported in one form or another by many formal notations intended for data or knowledge modelling. This paper presents an overview of various manifestations of classification mechanisms. Further, characteristic features of classification, such as the form of inheritance allowed from classes to instances, having single or multiple classifications and the structure of the classification hierarchy are identified, discussed, and contrasted. The paper also describes the classification mechanism offered by the knowledge representation language Telos. In Telos, classification is stratified and applicable not only to objects but also to (binary) relationships. The paper argues that these features lead to a more expressive notation, acquired at relatively modest conceptual and computational costs.

We present a framework for the development of information systems based on the premise that the knowledge that influences the development process needs to somehow be captured, represented, and managed if the development process is to be rationalized. Experiences with a prototype environment developed in ESPRIT project DAIDA demonstrate the approach. The project has implemented an environment based on state-of-the-art languages for requirements modeling, design and implementation of information systems. In addition, the environment offers tools for aiding the mapping process from requirements to design and then to implementation, also for representing decisions reached during the development process. The development process itself is represented explicitly within the system, thus making the DAIDA development framework easier to comprehend, use, and modify.

We describe Telos, a language intended to support the development of information systems. The design principles for the language are based on the premise that information system development is knowledge intensive and that the primary responsibility of any language intended for the task is to be able to formally represent the relevent knowledge. Accordingly, the proposed language is founded on concepts from knowledge representations. Indeed, the language is appropriate for representing knowledge about a variety of worlds related to a particular information system, such as the subject world (application domain), the usage world (user models, environments), the system world (software requirements, design), and the development world (teams, metodologies). We introduce the features of the language through examples, focusing on those provided for desribing metaconcepts that can then be used to describe knowledge relevant to a particular information system. Telos' fetures include an object-centered framework which supports aggregation, generalization, and classification; a novel treatment of attributes; an explicit representation of time; and facilities for specifying integrity constraints and deductive rules. We review actual applications of the language through further examples, and we sketch a formalization of the language.

The features of a compiler for the Taxis design language are described and discussed. Taxis offers an entity-based framework for designing interactive information systems and supports generalisation, classification and aggregation as abstraction mechanisms. Its features include multiple inheritance of attributes, isA hierarchies of transactions, metaclasses, typed attributes, a procedural exception-handling mechanism and an iteration construct based on the abstraction mechanisms supported Developing a compiler for the language involved dealing with the problems of efficiently representing and accessing a large collection of entities, performing (static) type checking and representing isA hierarchies of transactions.

TAXIS, a language for the design of interactive information systems (e.g., credit card verification, student-course registration, and airline reservations) is described. TAXIS offers (relational) database management facilities, a means of specifying semantic integrity constraints, and an exception-handling mechanism, integrated into a single language through the concepts of class, property , and the IS-A (generalization) relationship . A description of the main constructs of TAXIS is included and their usefulness illustrated with examples.

This paper describes TAXIS, a language for the design of Interactive Information Systems (e.g., credit card varification, student-course registration and airline reservations). TAXIS offers (relational) database management facilities, a means of specifying semantic integrity constraints and an exception-handling mechanism, integrated into a single language through the concepts of class, property and the ISA (generalization) relationship. The paper includes a description of the main constructs of TAXIS and illustrates their usefulness with examples.

This paper presents a semantic model of data bases. The model assumes the availability of a semantic network storing knowledge about a data base and a set of attributes for the data base. The use of the semantic net in generating a relational schema for the data base, in defining a set of semantic operators and in maintaining the data base consistent is then demonstrated.