The role of ontology in information management

The question posed in this thesis is how the use of ontologies by information systems affects their development and their performance. Several aspects about ontologies are presented, namely design and implementation issues, representational languages, and tools for ontology manipulation. The effects of the combination of ontologies and information systems are then investigated. An ontology-based tool to identify email message features is presented, and its implementation and execution details are discussed. The use of ontologies by information systems provides a better understanding about their requirements, reduces their development time, and supports knowledge management during execution time

A Multi-Agent Architecture for Distributed Domain-Specific Information Integration

On both the public Internet and private Intranets, there is a vast amount of data available that is owned and maintained by different organizations, distributed all around the world. These data resources are rich and recent; however, information gathering and knowledge discovery from them, in a particular knowledge domain, confronts major difficulties. The objective of this article is to introduce an autonomous methodology to provide for domain-specific information gathering and integration from multiple distributed sources

Aggressive aggregation

Among the first steps in a compilation pipeline is the construction of an Intermediate Representation (IR), an in-memory representation of the input program. Any attempt to program optimisation, both in terms of size and running time, has to operate on this structure. There may be one or multiple such IRs, however, most compilers use some form of a Control Flow Graph (CFG) internally. This representation clearly aims at general-purpose programming languages, for which it is well suited and allows for many classical program optimisations. On the other hand, a growing structural difference between the input program and the chosen IR can lose or obfuscate information that can be crucial for effective optimisation. With today’s rise of a multitude of different programming languages, Domain-Specific Languages (DSLs), and computing platforms, the classical machine-oriented IR is reaching its limits and a broader variety of IRs is needed. This realisation yielded, e.g., Multi-Level Intermediate Representation (MLIR), a compiler framework that facilitates the creation of a wide range of IRs and encourages their reuse among different programming languages and the corresponding compilers. In this modern spirit, this dissertation explores the potential of Algebraic Decision Diagrams (ADDs) as an IR for (domain-specific) program optimisation. The data structure remains the state of the art for Boolean function representation for more than thirty years and is well-known for its optimality in size and depth, i.e. running time. As such, it is ideally suited to represent the corresponding classes of programs in the role of an IR. We will discuss its application in a variety of different program domains, ranging from DSLs to machine-learned programs and even to general-purpose programming languages. Two representatives for DSLs, a graphical and a textual one, prove the adequacy of ADDs for the program optimisation of modelled decision services. The resulting DSLs facilitate experimentation with ADDs and provide valuable insight into their potential and limitations: input programs can be aggregated in a radical fashion, at the risk of the occasional exponential growth. With the aggregation of large Random Forests into a single aggregated ADD, we bring this potential to a program domain of practical relevance. The results are impressive: both running time and size of the Random Forest program are reduced by multiple orders of magnitude. It turns out that this ADD-based aggregation can be generalised, even to generaliii purpose programming languages. The resulting method achieves impressive speedups for a seemingly optimal program: the iterative Fibonacci implementation. Altogether, ADDs facilitate effective program optimisation where the input programs allow for a natural transformation to the data structure. In these cases, they have proven to be an extremely powerful tool for the optimisation of a program’s running time and, in some cases, of its size. The exploration of their potential as an IR has only started and deserves attention in future research

Survey over Existing Query and Transformation Languages

A widely acknowledged obstacle for realizing the vision of the Semantic Web is the inability of many current Semantic Web approaches to cope with data available in such diverging representation formalisms as XML, RDF, or Topic Maps. A common query language is the first step to allow transparent access to data in any of these formats. To further the understanding of the requirements and approaches proposed for query languages in the conventional as well as the Semantic Web, this report surveys a large number of query languages for accessing XML, RDF, or Topic Maps. This is the first systematic survey to consider query languages from all these areas. From the detailed survey of these query languages, a common classification scheme is derived that is useful for understanding and differentiating languages within and among all three areas

SEMANTIC WEB КАК НОВАЯ МОДЕЛЬ ИНФОРМАЦИОННОГО ПРОСТРАНСТВА ИНТЕРНЕТ

Описаны базовые концепции и архитектура Semantic Web, а также положение дел по разработке данного проекта по состоянию на конец 2007 года. Выделены проблемы, которые стоят перед мировым сообществом для дальнейшего развития Semantic Web.\ud Basic concepts and architecture of Semantic Web is described. State of the art concerning development of the project up to the end of 2007 year is outlined. The problems of future development of Semantic Web are noted.\u

1st international semantic web working symposium (SWWS-1)

euzenat2001hNo abstract available

Semantic web как новая модель информационного пространства интернет

Описаны базовые концепции и архитектура Semantic Web, а также положение дел по разработке данного проекта по состоянию на конец 2007 года. Выделены проблемы, которые стоят перед мировым сообществом для дальнейшего развития Semantic WebBasic concepts and architecture of Semantic Web is described. State of the art concerning development of the project up to the end of 2007 year is outlined. The problems of future development of Semantic Web are noted

Computer vision-based wood identification and its expansion and contribution potentials in wood science: A review

The remarkable developments in computer vision and machine learning have changed the methodologies of many scientific disciplines. They have also created a new research field in wood science called computer vision-based wood identification, which is making steady progress towards the goal of building automated wood identification systems to meet the needs of the wood industry and market. Nevertheless, computer vision-based wood identification is still only a small area in wood science and is still unfamiliar to many wood anatomists. To familiarize wood scientists with the artificial intelligence-assisted wood anatomy and engineering methods, we have reviewed the published mainstream studies that used or developed machine learning procedures. This review could help researchers understand computer vision and machine learning techniques for wood identification and choose appropriate techniques or strategies for their study objectives in wood science.This study was supported by Grants-in-Aid for Scientifc Research (Grant Number H1805485) from the Japan Society for the Promotion of Science

Pyrite mega-analysis reveals modes of anoxia through geological time

The redox structure of the water column in anoxic basins through geological time remains poorly resolved despite its importance to biological evolution/extinction and biogeochemical cycling. Here, we provide a temporal record of bottom and pore water redox conditions by analyzing the temporal distribution and chemistry of sedimentary pyrite. We combine machine-reading techniques, applied over a large library of published literature, with statistical analysis of element concentrations in databases of sedimentary pyrite and bulk sedimentary rocks to generate a scaled analysis spanning the majority of Earth’s history. This analysis delineates the prevalent anoxic basin states from the Archaean to present day, which are associated with diagnostic combinations of five types of syngenetic pyrite. The underlying driver(s) for the pyrite types are unresolved but plausibly includes the ambient seawater inventory, precipitation kinetics, and the (co)location of organic matter degradation coupled to sulfate reduction, iron (oxyhydr)oxide dissolution, and pyrite precipitation

Improving Throughput and Predictability of High-volume Business Processes Through Embedded Modeling

Being faster is good. Being predictable is better. A faithful model of a system, loaded to reflect the system\u27s current state, can then be used to look into the future and predict performance. Building faithful models of processes with high degrees of uncertainty can be very challenging, especially where this uncertainty exists in terms of processing times, queuing behavior and re-work rates. Within the context of an electronic, multi-tiered workflow management system (WFMS) the author builds such a model to endogenously quote due dates. A WFMS that manages business objects can be recast as a flexible flow shop in which the stations that a job (representing the business object) passes through are known and the jobs in the stations queues at any point are known. All of the other parameters associated with the flow shop, including job processing times per station, and station queuing behavior are uncertain though there is a significant body of past performance data that might be brought to bear. The objective, in this environment, is to meet the delivery date promised when the job is accepted. To attack the problem the author develops a novel heuristic algorithm for decomposing the WFMS\u27s event logs exposing non-standard queuing behavior, develops a new simulation component to implement that behavior, and assembles a prototypical system to automate the required historical analysis and allow for on-demand due date quoting through the use of embedded discrete event simulation modeling. To attack the problem the author develops a novel heuristic algorithm for decomposing the WFMS\u27s event logs exposing non-standard queuing behavior, develops a new simulation component to implement that behavior, and assembles a prototypical system to automate the required historical analysis and allow for on-demand due date quoting through the use of embedded discrete event simulation modeling. The developed software components are flexible enough to allow for both the analysis of past performance in conjunction with the WFMS\u27s event logs, and on-demand analysis of new jobs entering the system. Using the proportion of jobs completed within the predicted interval as the measure of effectiveness, the author validates the performance of the system over six months of historical data and during live operations with both samples achieving the 90% service level targeted