• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.3
• /
• pp.1327-1335
• /
• 2011

XML is good at representing data with hierarchical and self-describing structure. There is no inherent semantics with XML. However, semantics of XML has come up with us as XML is used in wide and advanced applications. This paper surveyed semantics in XML data processing environment. XML semantics can be categorized into four groups according to its usage; structural semantics, relational semantics, extended semantics, and semantic web. Relational database is still a good alternative for storing and managing large volume of XML documents. We propose an extended relational semantics in order to exploit it in managing XML documents such as query processing.

• Asia pacific journal of information systems
• /
• v.7 no.3
• /
• pp.167-180
• /
• 1997

Data semantics is an well recognized issue in areas of information systems research. It provides indispensable information for management of data, It describes what data mean, how they are created, where they can be applied to, to name a few. Because of these diverse nature of data semantics, it has been described from different perspectives of formalization. This article proposes to formalize data semantics by the processes that data are created or transformed, A scheme is proposed to describe the structure that data are created and transformed, which is called Bill of Data. Bill of Data is a directed graph, whose leaves are primary input data and whose internal nodes are output data objects produced from input data objects. Using Bill of Data, algorithms are developed to compare data semantics.

• The Journal of Information Technology and Database
• /
• v.7 no.1
• /
• pp.55-65
• /
• 2000

Information semantics is a well-known issue in areas of information systems researches. It describes what data mean, how they are created, where they can be applied to ; thus, it provides indispensable information for management of data. This article proposes to formalize information semantics by the processes that data are created or transformed. A scheme is proposed to describe an information production structure, which is called an information structure graph. An information structure graph is a directed graph, whose leaves are primary input data objects and whose root and internal nodes are output objects. Information semantics is derived from an information structure graph that has data as its root. For this, rules are proposed to manipulate and compare graphs. The structural relationships among information structure graphs are mapped into semantic relationships among data.

• Journal of the Korean Society for Library and Information Science
• /
• v.56 no.1
• /
• pp.95-117
• /
• 2022

This study developed and evaluated audio-visual (AV) semantics-based video summarization methods using eye tracking and electroencephalography (EEG) data. For this study, twenty-seven university students participated in eye tracking and EEG experiments. The evaluation results showed that the average recall rate (0.73) of using both EEG and pupil diameter data for the construction of a video summary was higher than that (0.50) of using EEG data or that (0.68) of using pupil diameter data. In addition, this study reported that the reasons why the average recall (0.57) of the AV semantics-based personalized video summaries was lower than that (0.69) of the AV semantics-based generic video summaries. The differences and characteristics between the AV semantics-based video summarization methods and the text semantics-based video summarization methods were compared and analyzed.

• The Journal of Korea Robotics Society
• /
• v.14 no.4
• /
• pp.340-347
• /
• 2019

Due to advances in machine intelligence and increased demands for autonomous machines, the complexity of the underlying software platform is increasing at a rapid pace, overwhelming the developers with implementation details. We attempt to ease the burden that falls onto the developers by creating a graphical programming framework we named Splash. Splash is designed to provide an effective programming abstraction for autonomous machines that require stream processing. It also enables programmers to specify genuine, end-to-end timing constraints, which the Splash framework automatically monitors for violation. By utilizing the timing constraints, Splash provides three key language semantics: timing semantics, in-order delivery semantics, and rate-controlled data-driven stream processing semantics. These three semantics together collectively serve as a conceptual tool that can hide low-level details from programmers, allowing developers to focus on the main logic of their applications. In this paper, we introduce the three-language semantics in detail and explain their function in association with Splash's language constructs. Furthermore, we present the internal workings of the Splash programming framework and validate its effectiveness via a lane keeping assist system.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2014.11a
• /
• pp.137-139
• /
• 2014

Objective: Data exchange, interoperability, and access as a service in healthcare information management systems (HIMS) is the basic need to provision health-services. Data existing in various HIMS not only differ in the basic underlying structure but also in data processing systems. Data interoperability can only be achieved when following a common structure or standard which is shareable such as semantics based structures. We propose web-enabler: A Hadoop MapReduce based distributed approach to transform the existing huge variety data in variety formats to a conformed and flexible ontological format that enables easy access to data, sharing, and providing various healthcare services. Results: For proof of concept, we present a case study of general patient record in conventional system to be enabled for analysis on the web by transforming to semantics based structure. Conclusion: This work achieves transformation of stale as well as future data to be web-enabled and easily available for analytics in healthcare systems.

• Language and Information
• /
• v.9 no.1
• /
• pp.69-92
• /
• 2005

Pattern recognition in cognitive agents is based on (i) the uninterpreted input data (e.g. parameter values) provided by the agent's hardware devices and (ii) and interpreted patterns (e.g. templates) provided by the agent's memory. Computationally, the task consists in finding the memory data corresponding best to the input data, for any given input. Once the best fitting memory data have been found, the input is recognized by applying to it the interpretation which happens to be stored with the memorized pattern. This paper presents a fast converging procedure which starts from a few initially recognized items and then analyzes the remainder of the input by systematically checking for items shown by memory to have been related to the initial items in previous encounters. In this way, known patterns are tried first, and only when they have been exhausted, an elementary exploration of the input is commenced. Efficiency is improved further by choosing the candidate to be tested next according to frequency.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.9 no.2
• /
• pp.422-430
• /
• 2008

Data integration is techniques to combine heterogeneous data from different sources, and to allow users to transparently access all data from multiple sources via a single view. The difficulty with data integration is data heterogeneity (i.e. schema heterogeneity, semantic heterogeneity). Richer semantics of data is a major factor in resolving conflicts among heterogeneous data sources. As UML class model represents only schema-based semantics of data, alternative methods such as ontology is useful for representing additional semantics. This paper proposes a method for integrating two data sources with UML class models by using an analysis of their ontologies. In our framework, ontology will be applied to describe semantics of data in each source. Then the ontologies are analysed and compared to determine their similarities and differences. The result of the comparison is used to devise an integrated ontology that will enable querying on the integrated information.

• Journal of KIBIM
• /
• v.6 no.3
• /
• pp.34-41
• /
• 2016

The previous studies argue that using the semantic properties of BIM objects is efficient for simulating the behaviors of autonomous, computer agents, called virtual-users, but such assumption is not proven via evidence-based research approaches. Hence, this present study aims to investigate the empirical effects of a human behavior simulation model equipped the semantics of spaces on the architecture-major students' operation and understanding of the simulation system, compared to a typical path-finding model. To achieve the aim, this study analyzed the survey and interview data, collected in the authentic design projects. The analysis indicates that (1) using a simulation model equipped the semantics of spaces helps the students' operation of the simulation, and (2) it also aids understanding the relationship between the variables of spaces and virtual-users (${\alpha}=0.74$). In addition, the qualitative data inform that the advantages of the simulation model that computes the semantics of spaces stem in the automatic behavioral changes of massive numbers of virtual-users, and efficient detection and activation on the what-if situations. The analysis also reveals that the simulation model has shortcomings in orchestrating the complex data structure between the semantics properties of spaces and virtual-users under multi-sequential scenarios. The results of this study contribute to develop a future design system combining BIM with human behavior simulation.

• Proceedings of the Korean Society for Language and Information Conference
• /
• 2002.02a
• /
• pp.2-27
• /
• 2002

As pact of a long-ranged project that aims at establishing database-theoretic semantics as a model of computational semantics, this presentation focuses on the development of a syntactic component for processing strings of words or sentences to construct semantic data structures. For design arid modeling purposes, the present treatment will be restricted to the analysis of some problematic constructions of Korean involving semi-free word order, conjunction arid temporal anchoring, and adnominal modification and antecedent binding. The present work heavily relies on Hausser's (1999, 2000) SLIM theory for language that is based on surface compositionality, time-linearity arid two other conditions on natural language processing. Time-linear syntax for natural language has been shown to be conceptually simple and computationally efficient. The associated semantics is complex, however, because it must deal with situated language involving interactive multi-agents. Nevertheless, by processing input word strings in a time-linear mode, the syntax cart incrementally construct the necessary semantic structures for relevant queries and valid inferences. The fragment of Korean syntax will be implemented in Malaga, a C-type implementation language that was enriched for both programming and debugging purposes arid that was particluarly made suitable for implementing in Left-Associative Grammar. This presentation will show how the system of syntactic rules with constraining subrules processes Korean sentences in a step-by-step time-linear manner to incrementally construct semantic data structures that mainly specify relations with their argument, temporal, and binding structures.