A Formal Framework for Linguistic Annotation

`Linguistic annotation' covers any descriptive or analytic notations applied to raw language data. The basic data may be in the form of time functions -- audio, video and/or physiological recordings -- or it may be textual. The added notations may include transcriptions of all sorts (from phonetic features to discourse structures), part-of-speech and sense tagging, syntactic analysis, `named entity' identification, co-reference annotation, and so on. While there are several ongoing efforts to provide formats and tools for such annotations and to publish annotated linguistic databases, the lack of widely accepted standards is becoming a critical problem. Proposed standards, to the extent they exist, have focussed on file formats. This paper focuses instead on the logical structure of linguistic annotations. We survey a wide variety of existing annotation formats and demonstrate a common conceptual core, the annotation graph. This provides a formal framework for constructing, maintaining and searching linguistic annotations, while remaining consistent with many alternative data structures and file formats.Comment: 49 page

Analysis of Decision Support Systems of Industrial Relevance: Application Potential of Fuzzy and Grey Set Theories

The present work articulates few case empirical studies on decision making in industrial context. Development of variety of Decision Support System (DSS) under uncertainty and vague information is attempted herein. The study emphases on five important decision making domains where effective decision making may surely enhance overall performance of the organization. The focused territories of this work are i) robot selection, ii) g-resilient supplier selection, iii) third party logistics (3PL) service provider selection, iv) assessment of supply chain’s g-resilient index and v) risk assessment in e-commerce exercises. Firstly, decision support systems in relation to robot selection are conceptualized through adaptation to fuzzy set theory in integration with TODIM and PROMETHEE approach, Grey set theory is also found useful in this regard; and is combined with TODIM approach to identify the best robot alternative. In this work, an attempt is also made to tackle subjective (qualitative) and objective (quantitative) evaluation information simultaneously, towards effective decision making. Supplier selection is a key strategic concern for the large-scale organizations. In view of this, a novel decision support framework is proposed to address g-resilient (green and resilient) supplier selection issues. Green capability of suppliers’ ensures the pollution free operation; while, resiliency deals with unexpected system disruptions. A comparative analysis of the results is also carried out by applying well-known decision making approaches like Fuzzy- TOPSIS and Fuzzy-VIKOR. In relation to 3PL service provider selection, this dissertation proposes a novel ‘Dominance- Based’ model in combination with grey set theory to deal with 3PL provider selection, considering linguistic preferences of the Decision-Makers (DMs). An empirical case study is articulated to demonstrate application potential of the proposed model. The results, obtained thereof, have been compared to that of grey-TOPSIS approach. Another part of this dissertation is to provide an integrated framework in order to assess gresilient (ecosilient) performance of the supply chain of a case automotive company. The overall g-resilient supply chain performance is determined by computing a unique ecosilient (g-resilient) index. The concepts of Fuzzy Performance Importance Index (FPII) along with Degree of Similarity (DOS) (obtained from fuzzy set theory) are applied to rank different gresilient criteria in accordance to their current status of performance. The study is further extended to analyze, and thereby, to mitigate various risk factors (risk sources) involved in e-commerce exercises. A total forty eight major e-commerce risks are recognized and evaluated in a decision making perspective by utilizing the knowledge acquired from the fuzzy set theory. Risk is evaluated as a product of two risk quantifying parameters viz. (i) Likelihood of occurrence and, (ii) Impact. Aforesaid two risk quantifying parameters are assessed in a subjective manner (linguistic human judgment), rather than exploring probabilistic approach of risk analysis. The ‘crisp risk extent’ corresponding to various risk factors are figured out through the proposed fuzzy risk analysis approach. The risk factor possessing high ‘crisp risk extent’ score is said be more critical for the current problem context (toward e-commerce success). Risks are now categorized into different levels of severity (adverse consequences) (i.e. negligible, minor, marginal, critical and catastrophic). Amongst forty eight risk sources, top five risk sources which are supposed to adversely affect the company’s e-commerce performance are recognized through such categorization. The overall risk extent is determined by aggregating individual risks (under ‘critical’ level of severity) using Fuzzy Inference System (FIS). Interpretive Structural Modeling (ISM) is then used to obtain structural relationship amongst aforementioned five risk sources. An appropriate action requirement plan is also suggested, to control and minimize risks associated with e-commerce exercises

Analyzing decision making in software design

A model is given for the analysis of rationality in design decision making. We define a formal means for answering the query, To what extent has a designer, on a particular occasion, using an explicit definition of 'good', decided rationally?A decision rationality classification scheme is proposed. This scheme incorporates non-compensatory decision analysis techniques (dominance and conjunctive cut-off) as well as compensatory techniques (simple and hierarchical additive weighting, linear assignment, concordance, and displaced ideal). A formal definition of design decision is derived by extending the Lehman, Stenning, Turski transformational model of the software design process. Their view of artifact specification mappings between linguistic systems is extended to include the concomitant effect of the mapping on resource expenditure.A formal specification for decision control knowledge is defined. This representation is the union of that knowledge required to support the various decision analysis techniques. Presumed to operationalize a designer's goals, the knowledge representation scheme includes five levels:1. Each objective expresses some relevant design concern for an artifact and/or resource characteristic.2. Each criterion expresses some relevant decomposition of a superior objective or criterion.3. Each attribute expresses the bottom-most decomposition for a superior criterion. Each attribute may have a weight indicating its relative contribution to its superior criterion.4. For each attribute, a value function expresses the designer's preference ordering over observed performance for an attribute.5. For each attribute, an observation channel describes an observer independent metric over some specification (either resource or artifact) rendered in some linguistic system and a procedure for application of that metric.Our model is applied to problems in Structured Design and conceptual data modeling. We argue that a comprehensive design history must include not only the transformations applied but also the rationale used in deciding their application. This rationale must include decision control knowledge governing both artifact (product) and resource (process) facets of design decision making. The principal contribution of this work is that the opacity of the decision intensive aspects of design are reduced thereby taking a necessary step for increasing the efficiency and effectiveness of software development

Hierarchical Concurrent Engineering in a Multiagent Framework

Our experience indicates coordination in concurrent engineering (CE) requires support for two types of relationships among decision makers supervisor/subordinate and peer-to-peer Supervisor/subordinate relationships are created by the standard hierarchical decomposition process that is required to solve any large design problem Peer-to-peer relationships arise when teams of decision makers must interact, without direct guidance, to achieve individual and common goals In this paper, we describe a general decision-making methodology, which we call hierarchical CE The emphasis of hierarchical CE is to provide support for both supervisor/subordinate and peer-to-peer relationships In addition to the concept of hierarchical CE, we present a supporting agent-based framework in which the preferences and constraints of a design supervi sor are distributed to design subordinates, who are expected to exploit their local expertise within the context provided by this global information A distinct separation between feasibility and value facilitates optimal decision-making by design agents, since the bounds on feasibility do not include arbitrary statements about value This distinction may prove useful for other problem domains as wellPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/68258/2/10.1177_1063293X9600400105.pd

A MAUT approach for reusing ontologies

Knowledge resource reuse has become a popular approach within the ontology engineering field, mainly because it can speed up the ontology development process, saving time and money and promoting the application of good practices. The NeOn Methodology provides guidelines for reuse. These guidelines include the selection of the most appropriate knowledge resources for reuse in ontology development. This is a complex decision-making problem where different conflicting objectives, like the reuse cost, understandability, integration workload and reliability, have to be taken into account simultaneously. GMAA is a PC-based decision support system based on an additive multi-attribute utility model that is intended to allay the operational difficulties involved in the Decision Analysis methodology. The paper illustrates how it can be applied to select multimedia ontologies for reuse to develop a new ontology in the multimedia domain. It also demonstrates that the sensitivity analyses provided by GMAA are useful tools for making a final recommendation

Multicriteria Methodology for the NEEDS Project

This report begins with an overview of multicriteria analysis methods, and the basic principles of developing mathematical models for such analysis. An overview of various representation of user preferences is then presented, including methods based on pairwise comparisons of criteria and those based on scalarizing functions. This is followed by a summary of structures of criteria and alternatives. Next, basic properties of multi-criteria analysis are discussed, followed by a more detailed presentation of the similarities of and differences between the main methods based on scalarizing functions. This report concludes that existing methods do not best meet the needs of the NEEDS project, presents the reasons, and proposes a new methodology for development. Depending upon the development and testing of this new methodology, an existing method will also be chosen as a backup for comparative or alternate use

Methodological review of multicriteria optimization techniques: aplications in water resources

Multi-criteria decision analysis (MCDA) is an umbrella approach that has been applied to a wide range of natural resource management situations. This report has two purposes. First, it aims to provide an overview of advancedmulticriteriaapproaches, methods and tools. The review seeks to layout the nature of the models, their inherent strengths and limitations. Analysis of their applicability in supporting real-life decision-making processes is provided with relation to requirements imposed by organizationally decentralized and economically specific spatial and temporal frameworks. Models are categorized based on different classification schemes and are reviewed by describing their general characteristics, approaches, and fundamental properties. A necessity of careful structuring of decision problems is discussed regarding planning, staging and control aspects within broader agricultural context, and in water management in particular. A special emphasis is given to the importance of manipulating decision elements by means ofhierarchingand clustering. The review goes beyond traditionalMCDAtechniques; it describes new modelling approaches. The second purpose is to describe newMCDAparadigms aimed at addressing the inherent complexity of managing water ecosystems, particularly with respect to multiple criteria integrated with biophysical models,multistakeholders, and lack of information. Comments about, and critical analysis of, the limitations of traditional models are made to point out the need for, and propose a call to, a new way of thinking aboutMCDAas they are applied to water and natural resources management planning. These new perspectives do not undermine the value of traditional methods; rather they point to a shift in emphasis from methods for problem solving to methods for problem structuring. Literature review show successfully integrations of watershed management optimization models to efficiently screen a broad range of technical, economic, and policy management options within a watershed system framework and select the optimal combination of management strategies and associated water allocations for designing a sustainable watershed management plan at least cost. Papers show applications in watershed management model that integrates both natural and human elements of a watershed system including the management of ground and surface water sources, water treatment and distribution systems, human demands,wastewatertreatment and collection systems, water reuse facilities,nonpotablewater distribution infrastructure, aquifer storage and recharge facilities, storm water, and land use