• Asia pacific journal of information systems
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• v.2 no.2
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• pp.85-102
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• 1992

A deductive database consists of collection of stored facts and deductive rules. It can answer queries based on logical deduction from the stored facts and general rules. A deductive database has both a declarative meaning(semantics) and a procedural meaning. The declarative semantics of a deductive database provides a definition of the meaning of the program in a manner which is independent of procedural considerations, context-free, and easy to manipulate, exchange and reason about. This paper investigates various declarative semantics of deductive databases, dicusses related computational issues, and suggests another declarative semantics for deductive databases which is more practical than others.

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

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.243-250
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• 2002

In order to properly interpret and process or operators in deductive databases including indefinite clauses, we propose to use Lasez′s Strong Model Semantics(LSMS) which is reasonably simple yet powerful enough to support both exclusive and inclusive interpretations. Conventional semantics either fail to support both interpretations or simply too complex. Therefore, in this paper we study advantages and difficulties of representing indefinite information, and as for the solution to difficulties, we show how LSMS can be used to support both inclusive or and exclusive or interpretations. We also investigate and analyze it′s properties and show how it semantically differs from others. We believe that LSMS is the only "reasonably simple" semantics that supports both inclusive and exclusive interpretations.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.148-154
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• 2010

In the study of the formal semantics of uncertain databases, we typically take an algebraic approach by mapping an uncertain database to possible worlds which are a set of relational databases. In this paper, we present a new semantics for uncertain databases which takes a logical approach by translating uncertain databases into logical theories. A characteristic feature of our semantics is that it uses linear logic, instead of propositional logic, as its logical foundation. Linear logic is suitable for a logical interpretation of uncertain information because unlike propositional logic, it treats logical formulae not as persistent facts but as consumable resources. As the main result, we show that our semantics is faithful to the operational account of uncertain databases in the algebraic approach.

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

• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.457-483
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• 2007

Database Semantics (DBS) attempts to provide a comprehensive and integrated approach to human communication which seeks theory-implementation transparency. Two key components of DBS are Word bank as a data structure and left-Associative Grammar (LAG) as an algorithm. This study aims to provide a pilot implementation of Korean in DBS. First, it is shown how the three separate modules of grammar in DBS, namely, Hear, Think, and Speak, combine to form an integrated system that simulates a cognitive agent by making use of a simple Korean sentence as an example. Second, we provide a detailed analysis of the structure in Korean that is a characteristic of Korean involving numerals, classifiers, and nouns, thereby illustrating how DBS can be applied to Korean. We also discuss an issue raised in the literature concerning a problem that arises when we try to apply the LAG algorithm to the analysis of head-final language like Korean, and then discuss some possible solution to the problem.

• Language and Information
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• v.19 no.2
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• pp.1-18
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• 2015

This paper retraces the development of Database Semantics (DBS) from its beginnings in Montague grammar. It describes the changes over the course of four decades and explains why they were seen to be necessary. DBS was designed to answer the central theoretical question for building a talking robot: How does the mechanism of natural language communication work? For doing what is requested and reporting what is going on, a talking robot requires not only language but also non-language cognition. The contents of non-language cognition are re-used as the meanings of the language surfaces. Robot-externally, DBS handles the language-based transfer of content by using nothing but modality-dependent unanalyzed external surfaces such as sound shapes or dots on paper, produced in the speak mode and recognized n the hear mode. Robot-internally, DBS reconstructs cognition by integrating linguistic notions like functor-argument and coordination, philosophical notions like concept-, pointer-, and baptism-based reference, and notions of computer science like input-output, interface, data structure, algorithm, database schema, and functional flow.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.53-63
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• 2011

Many techniques have been proposed to store and query XML data efficiently. One way achieving this goal is using relational database by transforming XML data into relational format. It is important to transform schema to preserve the content, the structure and the constraints of the semantics information of the XML document. Especially, key constraints are an important part of database theory. Therefore, the proposal technique has considered the semantics of XML as expressed by primary keys and foreign keys. And, the proposal technique can preserve not only XML data constraints but also the content and the structure and the semantics of XML data thru transformation process. Transforming information is the content and the structure of the document(the parent-child relationship), the functional dependencies, semantics of the document as captured by XML key and keyref constraints. Because of XML schema transformation ensures that preserving semantic constraints, the advantages of these transformation techniques do not need to use the stored procedure or trigger which these data ensures data integrity in the relational database. In this paper, there is not chosen the ID/IDREF key which supported in DTD, the inheritance relationship, the implicit referential integrity.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.11-20
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• 1999

Because conventional spatial databases process the spatial information that is valid at current time, it is difficult to manage historical information efficiently which has been changed from the past to current. Recently, there are rapid increasing of interest to solve this problem so that makes databases to support historical information as well as spatial management at the same time. It can be eventually used in a various application areas. The formal semantics in a database is used to represent database structures and operations in order to prove the correctiveness of them in terms or mathematics. It also plays an important role in database to design a database and database management system. So in this paper, we suggest spatiotemporal domain, object, data, and spatiotemporal geometric/topological operations. And we not only formalize relational algebra/calculus using formal semantics for a spatiotemporal data model, but also show the example of real orld with them.

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