Navy Messaging Analytics to Improve Readiness, Response and Preparedness

2022 | HICSS | Citations: 0

Authors: Dilmaghani, Raheleh; Turco, Kyle; Diego, San

Abstract: There are tens of thousands of official messages exchanged within the Navy’s mess ... Expand

Abstract: There are tens of thousands of official messages exchanged within the Navy’s messaging system daily. The messages carry a tremendous amount of data that is not fully processed nor analyzed. If we could enhance extracting the value of these data, and automate, we could improve speed, readiness, performance, maintenance, outage scheduling, and much more. Although messages follow a prescribed format, it is not uniform across the message types and data entry is not enforced and prone to human interpretation or error in containing all relevant information and correct categorization or labeling. Often there is relevant information in other messages not directly linked or referenced, but if inferred could enhance the observer’s perspective and response to the situation. By analyzing the massive data stored within Navy tactical messages, we could learn about fleet readiness without asking a particular unit or group, “are you ready?” Better yet, we may be able to predict future readiness based on past schedule and performance data if correlated correctly to learn patterns that indicate future mission success. In this paper, we present results from a pilot project where we show the significance of processing available messages for relevant information by not limiting the message types that seem to be the right category or to those with an explicit keyword. This process helps to detect relevant information and create meaning correlations, which could contribute to more informed decision making or to provide the Commander information to make decisions proactively instead of reacting to negative outcomes like casualties or mishaps. Extracting relevant information in turn can contribute to more informed decision making in saving lives, reduced sustainment costs, or repair costs. Collapse

Topics: electronic mail Python analytical information system knowledge base automated reasoning

Methods: support vector machine machine learning logistic regression supervised learning natural language processing

Insider Threat Detection in PRODIGAL

2017 | HICSS | Citations: 0

Authors: Goldberg, Henry; Young, William; Reardon, Matthew; Phillips, Brian; Senator, Ted

Abstract: This paper reports on insider threat detection research, during which a prototyp ... Expand

Abstract: This paper reports on insider threat detection research, during which a prototype system (PRODIGAL)1 was developed and operated as a testbed for exploring a range of detection and analysis methods. The data and test environment, system components, and the core method of unsupervised detection of insider threat leads are presented to document this work and benefit others working in the insider threat domain. Collapse

Topics: insider threat database system information system use extract transform load process MySQL

Methods: machine learning experiment design artifact anomaly detection ensemble learning

AI capabilities and user experiences: a comparative study of user reviews for assistant and non-assistant mobile apps

2017 | Americas Conference on Information Systems | Citations: 0

Authors: Nguyen, Quynh N; Sidorova, Anna

Abstract: Inspired by the progress in the field of artificial intelligence and by the assi ... Expand

Abstract: Inspired by the progress in the field of artificial intelligence and by the assimilation of AI capabilities into a variety of IT applications, including personal assistant apps such as Siri, this study examines how user experiences with such assistant apps differs from their interactions with more traditional IT artifacts. Using text analysis of user reviews of 10 assistant and 15 non-assistant apps, we identify 50 topics that reflect user experiences and evaluations. Most identified topics map well into existing IS constructs, such as ease of use, system quality and affordances, suggesting that current IS theory adequately reflects user experiences with IT, and is relevant to the analysis of AI-enabled applications. The results also highlight differences in how users experience their interactions with assistant and non-assistant apps, pointing towards potential shifts in how we experience and theorize user-IT interactions in the AI-enabled world. Collapse

Topics: mobile application artificial intelligence user experience ease of use usability

Methods: design artifact latent semantic analysis natural language processing machine learning qualitative content analysis

Theories: information systems theory

On the Ontological Quality and Logical Quality of Conceptual-Modeling Grammars: The Need for a Dual Perspective

2016 | Information Systems Research | Citations: 0

Authors: Clarke, Roger; Burton-Jones, Andrew; Weber, Ron

Abstract: A core activity in information systems development involves building a conceptua ... Expand

Abstract: A core activity in information systems development involves building a conceptual model of the domain that an information system is intended to support. Such models are created using a conceptual-modeling (CM) grammar. Just as high-quality conceptual models facilitate high-quality systems development, high-quality CM grammars facilitate high-quality CM. This paper provides a new perspective on ways to improve the quality of the semantics of CM grammars. For many years, the leading approach to this topic has relied on ontological theory. We show, however, that the ontological approach captures only half the story; it needs to be coupled with a logical approach. We explain how the ontological and logical qualities of CM grammars interrelate. Furthermore, we outline three contributions of a logical approach to evaluating the quality of CM grammars: a means of seeing some familiar CM problems in simpler ways, illumination of new problems, and proving the benefit of modifying existing CM grammars in particular ways. We demonstrate these benefits in the context of the Entity-Relationship grammar. More generally, our paper opens a new area of research with many opportunities for future research and practice. Collapse

Topics: knowledge representation database system online learning system information system use relational database

Methods: ontological modelling conceptual modelling design science qualitative interview database modeling

Theories: cognitive theory

Improving the Semantics of Conceptual-Modeling Grammars: A New Perspective on an Old Problem

2013 | International Conference on Information Systems | Citations: 0

Authors: Clarke, Roger; Burton-Jones, Andrew; Weber, Ron

Abstract: A core activity in information systems development involves understanding the co ... Expand

Abstract: A core activity in information systems development involves understanding the conceptual model of the domain that the information system supports. Any conceptual model is ultimately created using a conceptual-modeling (CM) grammar. Accordingly, just as high quality conceptual models facilitate high quality systems development, high quality CM grammars facilitate high quality conceptual modeling. This paper seeks to provide a new perspective on improving the quality of CM grammar semantics. For the past twenty years, the leading approach to this topic has drawn on ontological theory. However, the ontological approach captures just half of the story. It needs to be coupled with a logical approach. We show how ontological quality and logical quality interrelate and we outline three contributions of a logical approach: the ability to see familiar conceptual-modeling problems in simpler ways, the illumination of new problems, and the ability to prove the benefit of modifying CM grammars. Collapse

Topics: knowledge representation predicate logic automated reasoning

Methods: conceptual modelling ontological modelling entity relationship modeling design science survey

Theories: theory of everything theory of ontological expressiveness

Special Issue on ‘Human Factors and Computational Models in Negotiation’

2012 | Group Decision and Negotiation | Citations: 0

Authors: Hindriks, Koen V.; Jonker, Catholijn M.

Abstract: Negotiation is a complex emotional decision-making process aiming to reach an a ... Expand

Abstract: Negotiation is a complex emotional decision-making process aiming to reach an agreement to exchange goods or services. Although a daily activity, few people are effective negotiators. Existing support systems make a significant improvement if the negotiation space is well-understood, because computers can better cope with the computational complexity. However, the negotiation space can only be properly developed if the human parties jointly explore their interests. The inherent semantic problem and the emotional issues involved make that negotiation cannot be handled by artificial intelligence alone, and a human-machine collaborative system is required. Everyone is an experienced negotiator and everyone has an opinion about their negotiation skills. However, even professional negotiators can still improve their skills considerably by using automated support for negotiation.Negotiation is a prime example of a task for which the human mind is but partially equipped, and for which artificial intelligence can only provide partial assistance. Computational power, data storage, search techniques, computational heuristics to tackle exponential problem spaces, are among the good products of AI. However, AI has not solved the problem of the huge amount of knowledge necessary to cope with, and understand arbitrary conversations and problems. The complexity and the variability of the problems humans wish to address are just too much to handle. It thus becomes important to both study the human factors as well as computational models that contribute to reaching negotiated agreements between parties.This special issue is a selection of papers that were presented at the First International Conference on Human Factors and Computational Models in Negotiation. These papers present various research goals, ideas, challenges and approaches towards creating the next generation of negotiation support systems. Collapse

Topics: automated reasoning

Methods: agent based simulation

Argumentation-Based Qualitative Preference Modelling with Incomplete and Uncertain Information

2012 | Group Decision and Negotiation | Citations: 0

Authors: Visser, Wietske; Hindriks, Koen V.; Jonker, Catholijn M.

Abstract: This paper presents an argumentation-based framework for the modelling of, and a ... Expand

Abstract: This paper presents an argumentation-based framework for the modelling of, and automated reasoning about multi-attribute preferences of a qualitative nature. The framework presents preferences according to the lexicographic ordering that is well-understood by humans. Preferences are derived in part from knowledge. Knowledge, however, may be incomplete or uncertain. The main contribution of the paper is that it shows how to reason about preferences when only incomplete or uncertain information is available. We propose a strategy that allows reasoning with incomplete information and discuss a number of strategies to handle uncertain information. It is shown how to extend the basic framework for modelling preferences to incorporate these strategies. Collapse

Topics: knowledge base decision making automated reasoning

Theories: argumentation theory

Suggestion Mining from Customer Reviews

2011 | Americas Conference on Information Systems | Citations: 0

Authors: Viswanathan, Amar; Venkatesh, Prasanna; Vasudevan, Bintu; Balakrishnan, Rajesh; Shastri, Lokendra

Abstract: The increasing online content has influenced users’ buying behavior. It has trig ... Expand

Abstract: The increasing online content has influenced users’ buying behavior. It has triggered a paradigm shift in marketing strategies, as the consumer is no longer swayed by marketers, instead relying on user comments for a particular product or service. This paper focuses on extracting information from feedbacks like suggestions and recommendation by the users that is often present along with the sentiment. While Sentiment Analysis looks at extraction of consumer sentiment, our focus is on extracting actionable feedback present in the text for use by different stakeholders like business analysts and the customer. Our focus is on mining the key suggestions present in text which would benefit the product developer. We present our results and observations in the paper. Collapse

Topics: knowledge representation mobile phone computer system automated reasoning online review

Methods: sentiment analysis ontological modelling product review

Context-Aware Adaptation: A Case Study On Mathematical Notations

2009 | Information Systems Management | Citations: 0

Authors: Müller, Christine; Kohlhase, Michael

Abstract: In the last two decades, the World Wide Web has become the universal information ... Expand

Abstract: In the last two decades, the World Wide Web has become the universal information source. Search engines can efficiently serve daily information needs due to the enormous redundancy of relevant resources on the web. For educational and scientific information needs, the web functions much less efficiently: Scientific publishing is built on a culture of unique reference publications, and moreover, documents abound with specialized structures such as technical nomenclature, notational conventions, references, tables, or graphs. Many of these structures are peculiar to specialized communities determined by nationality, research group membership, or adherence to a special school of thought. To keep the much-lamented “digital divide” from becoming a “cultural divide,” we have to make online material more accessible and adaptable to individual users. In this paper, we attack this goal for the field of mathematics where knowledge is abstract, highly structured, and extraordinarily interlinked. Modern, content-based representation formats like OpenMath or content MathML allow us to capture, model, relate, and represent mathematical knowledge object, and thus, make them context-aware and machine-adaptable to the respective user contexts. Building on previous work, which can make mathematical notations adaptable, we employ user modeling techniques to make them adaptive to relieve the reader of configuration tasks. We present a comprehensive framework for adaptive notation management and evaluate it on the proof-of-concept prototype panta rhei. Collapse

Topics: knowledge representation extensible markup language outsourcing user behavior usability

Methods: ontological modelling computational algorithm design artifact conceptual modelling qualitative interview

Theories: learning theory

A Semantic Approach to Secure Collaborative Inter- Organizational eBusiness Processes (SSCIOBP)

2008 | Journal of the Association for Information Systems | Citations: 0

Authors: D'Aubeterre, Fergle; Singh, Rahul; Iyer, Lakshmi

Abstract: The information supply chain (ISC) involves the exchange, organization, selectio ... Expand

Abstract: The information supply chain (ISC) involves the exchange, organization, selection, and synthesis of relevant knowledge and information about production, purchase planning, demand forecasting, and inventory among collaborating business partners in a value chain. Information and knowledge sharing in an ISC occurs in a business process context. Seamless knowledge exchange within and across organizations involved in secure business processes is critically needed to "secure and cultivate the information supply chain." Extant literature does not explicitly consider or systematically represent component knowledge, process knowledge and security knowledge for business processes within and across organizations. As a result, organizations engaged in collaborative inter-organizational processes continue to be plagued with issues such as semantic conflict issues, lack of integration of heterogeneous systems, and lack of security knowledge regarding authorized access to resources. Without appropriate security controls, manual interventions lead to unauthorized access to resources. These problems motivate our Semantic Approach to Secure Collaborative Inter-Organizational eBusiness Processes (SSCIOBP). We follow a design science paradigm to identify metarequirements of SSCIOBP and develop the design artifact. SSCIOBP is evaluated using observational and descriptive evaluation methods following Hevner et al. (2004). We apply our approach to show how the Collaborative Planning Forecasting and Replenishment (CPFR) industry standard models can be enhanced using the proposed design artifact. We apply SSCIOBP to a case study to illustrate its applicability in mapping core business processes of organizations to solve semantic inter-operability issues and systematically incorporate component, process and security knowledge in the design of secure business processes across the information supply chain. Collapse

Topics: business process management knowledge representation electronic business supply chain management access control

Methods: design artifact kernel theory case study design requirement meta design