scholarly journals Graph-Based Generation of Referring Expressions

2003 ◽  
Vol 29 (1) ◽  
pp. 53-72 ◽  
Author(s):  
Emiel Krahmer ◽  
Sebastiaan van Erk ◽  
André Verleg

This article describes a new approach to the generation of referring expressions. We propose to formalize a scene (consisting of a set of objects with various properties and relations) as a labeled directed graph and describe content selection (which properties to include in a referring expression) as a subgraph construction problem. Cost functions are used to guide the search process and to give preference to some solutions over others. The current approach has four main advantages: (1) Graph structures have been studied extensively, and by moving to a graph perspective we get direct access to the many theories and algorithms for dealing with graphs; (2) many existing generation algorithms can be reformulated in terms of graphs, and this enhances comparison and integration of the various approaches; (3) the graph perspective allows us to solve a number of problems that have plagued earlier algorithms for the generation of referring expressions; and (4) the combined use of graphs and cost functions paves the way for an integration of rule-based generation techniques with more recent stochastic approaches.

2019 ◽  
Vol 97 (Supplement_2) ◽  
pp. 61-62
Author(s):  
John Butler

Abstract Animal disease traceability—or knowing where diseased and at-risk animals are, where they’ve been, and when—is important to ensuring a rapid response when animal disease events take place. Although animal disease traceability does not prevent disease, an efficient and accurate traceability system reduces the number of animals and response time involved in a disease investigation; which, in turn, reduces the economic impact on owners and affected communities. The current approach to traceability in the United States is the result of significant discussion and compromise. Federal policy regarding traceability has been amended several times over the past decade based on stakeholder feedback, particularly from the cattle industry. In early 2010, USDA announced a new approach for responding to and controlling animal diseases, referred to as the ADT framework. USDA published a proposed rule, “Traceability for Livestock Moving Interstate,” on August 11, 2011, and the final rule on January 9, 2013. Under the final rule, unless specifically exempted, livestock moved interstate must be officially identified and accompanied by an interstate certificate of veterinary inspection (ICVI) or other documentation. However, these requirements do not apply to all cattle. Beef cattle under 18 months of age, unless they are moved interstate for shows, exhibitions, rodeos, or recreational events, are exempt from the official identification requirement in this rule. We can do better. Our industry must recognize how vulnerable we really are, should we be subject to a disease such as foot and mouth. We must also understand what a competitive disadvantage the United States faces in the global marketplace without a recognized, industry-wide traceability system.


2014 ◽  
Vol 40 (4) ◽  
pp. 883-920 ◽  
Author(s):  
Srinivasan Janarthanam ◽  
Oliver Lemon

We address the problem of dynamically modeling and adapting to unknown users in resource-scarce domains in the context of interactive spoken dialogue systems. As an example, we show how a system can learn to choose referring expressions to refer to domain entities for users with different levels of domain expertise, and whose domain knowledge is initially unknown to the system. We approach this problem using a three step process: collecting data using a Wizard-of-Oz method, building simulated users, and learning to model and adapt to users using Reinforcement Learning techniques. We show that by using only a small corpus of non-adaptive dialogues and user knowledge profiles it is possible to learn an adaptive user modeling policy using a sense-predict-adapt approach. Our evaluation results show that the learned user modeling and adaptation strategies performed better in terms of adaptation than some simple hand-coded baseline policies, with both simulated and real users. With real users, the learned policy produced around a 20% increase in adaptation in comparison to an adaptive hand-coded baseline. We also show that adaptation to users' domain knowledge results in improving task success (99.47% for the learned policy vs. 84.7% for a hand-coded baseline) and reducing dialogue time of the conversation (11% relative difference). We also compared the learned policy to a variety of carefully hand-crafted adaptive policies that employ the user knowledge profiles to adapt their choices of referring expressions throughout a conversation. We show that the learned policy generalises better to unseen user profiles than these hand-coded policies, while having comparable performance on known user profiles. We discuss the overall advantages of this method and how it can be extended to other levels of adaptation such as content selection and dialogue management, and to other domains where adapting to users' domain knowledge is useful, such as travel and healthcare.


2021 ◽  
Vol 20 (01) ◽  
pp. 2150013
Author(s):  
Mohammed Abu-Arqoub ◽  
Wael Hadi ◽  
Abdelraouf Ishtaiwi

Associative Classification (AC) classifiers are of substantial interest due to their ability to be utilised for mining vast sets of rules. However, researchers over the decades have shown that a large number of these mined rules are trivial, irrelevant, redundant, and sometimes harmful, as they can cause decision-making bias. Accordingly, in our paper, we address these challenges and propose a new novel AC approach based on the RIPPER algorithm, which we refer to as ACRIPPER. Our new approach combines the strength of the RIPPER algorithm with the classical AC method, in order to achieve: (1) a reduction in the number of rules being mined, especially those rules that are largely insignificant; (2) a high level of integration among the confidence and support of the rules on one hand and the class imbalance level in the prediction phase on the other hand. Our experimental results, using 20 different well-known datasets, reveal that the proposed ACRIPPER significantly outperforms the well-known rule-based algorithms RIPPER and J48. Moreover, ACRIPPER significantly outperforms the current AC-based algorithms CBA, CMAR, ECBA, FACA, and ACPRISM. Finally, ACRIPPER is found to achieve the best average and ranking on the accuracy measure.


1990 ◽  
Vol 206 ◽  
Author(s):  
Tongsan D. Xiao ◽  
Peter R. Strutt ◽  
Kenneth E. Gonsalves

ABSTRACTA new approach has been developed for the synthesis of nanoscale ceramic powder materials from liquid organosilazane precursors. This technique, by exploiting fast kinetic chemical and physical reactions, makes it possible to synthesize significant quantities of material in a relatively short time. In the current approach aerosols of a silazane monomer, (CH3SiHNH)n, (n = 3 or 4), of mol. wt. 280–320, are injected into the beam of a cw industrial CO2 laser to obtain nanoscale ceramic powders. Injection of the aerosol into the laser-beam results in a high-temperature plume. Rapid condensation of the molecular precursor species emerging from the laser plume results in the formation of preceramic polymer particles, with an average diameter of 62 nm. One attractive feature of this process is that 70 wt.% of the liquid precursor is converted into nanoscale powders. Another feature is that only a further 10 wt.% loss occurs during post thermal treatment to form the end-product.


Author(s):  
Antoni Ligęza ◽  
Jan Kościelny

A New Approach to Multiple Fault Diagnosis: A Combination of Diagnostic Matrices, Graphs, Algebraic and Rule-Based Models. The Case of Two-Layer ModelsThe diagnosis of multiple faults is significantly more difficult than singular fault diagnosis. However, in realistic industrial systems the possibility of simultaneous occurrence of multiple faults must be taken into account. This paper investigates some of the limitations of the diagnostic model based on the simple binary diagnostic matrix in the case of multiple faults. Several possible interpretations of the diagnostic matrix with rule-based systems are provided and analyzed. A proposal of an extension of the basic, single-level model based on diagnostic matrices to a two-level one, founded on causal analysis and incorporating an OR and an AND matrix is put forward. An approach to the diagnosis of multiple faults based on inconsistency analysis is outlined, and a refinement procedure using a qualitative model of dependencies among system variables is sketched out.


2018 ◽  
Author(s):  
Krisztian Magori

AbstractHaemaphysalis longicornis, the Asian longhorned (or bush) tick has been detected on a sheep in August 2017 in Hunterdon County, New Jersey. By October 26, 2018, this tick has been detected in 44 counties in 9 states along the Atlantic coast of the United States, with the first detection backdated to 2010. Here, I use a simple rule-based climate envelope model, based on a prior analysis in New Zealand, to provide a preliminary analysis of the potential range of this introduced tick species in North America. After validating this model against the counties where the tick has been already detected, I highlight the counties where this tick might cause considerable economic harm. I discuss the many limitations of this simple approach, and potential remedies for these limitations, and more sophisticated approaches. Finally, I conclude that substantial areas of the US, especially along the Gulf and Atlantic coast, are suitable for the establishment of this tick, putting millions of heads of livestock potentially at risk.


Author(s):  
Robert Chee Choong Gan ◽  
Christina May May Chin

Due to alarmingly high failure rates attributed to either a lack of project implementation or if implemented, poor results in organizations, many PM consulting organizations have begun developing their own PM maturity models (PM3) to assess organization maturity level, to identify their clients' PM maturity gap, and to provide a pathway by which their clients could move up the maturity scale and performance. Despite the many claims of PM3 assessment capabilities, the lack of success in market adoption of PM3 models suggests the need for more studies to identify if these are due to the many definition of project success, the lack of consensus of what the components of PM3 should be, or the increasing expectations of the PM community. Thus, this chapter aims to identify the reasons behind differing organizations' views on the dimension of project success, components of PM3's direct impact on organizational performance, and how PM maturity can be measured and correlated to the various level of organizational success with a new approach known as DPM3.


2020 ◽  
pp. 12-31
Author(s):  
Nicholas J. Saunders

This chapter looks at how the timely development of an interdisciplinary archaeology (modern conflict archaeology) of the First World War from the late 1990s offered a comprehensive and nuanced way of investigating the many interlocking military and cultural aspects of the Arab Revolt and its aftermath. Ephemeral archaeological traces in the sands of southern Jordan, it was hoped, would speak to the origins of modern guerrilla warfare which itself contributed to the shaping of the Middle East after 1918. The new approach showed the power of objects to create and transmit impressions and evaluations of the Revolt and its personalities—not least by the catalysing effects of finding similar items during excavations of the original landscapes whence all such objects derived their historical significance. The desert, so apparently empty of information and insight, would prove to be full of both. The key to deciphering its archaeological message lay in understanding the landscape, its layers and its objects—a quest which began with the largest artefact of all, the Hejaz Railway.


Crime Science ◽  
2019 ◽  
Vol 8 (1) ◽  
Author(s):  
Tarah Hodgkinson ◽  
Tullio Caputo ◽  
Michael L. McIntyre

Abstract In this conceptual piece, we argue that the current approach to police performance measurement typically based on the use of traditional police metrics has failed to achieve the desired results and that a different strategy is required. Traditional police metrics have a narrow focus on crime and the police response to it. They provide little information on how well police organizations are performing. Importantly, traditional police metrics do not incorporate input from police stakeholders in goal identification, nor do they use specifically designed indicators to assess progress towards achieving these goals. Following an analysis of the criticisms levelled at the use of traditional police metrics, and subsequent attempts to address these issues, we argue that a networked governance approach represents a more promising foundation for undertaking police organizational performance assessment. Such an approach would engage stakeholders more directly in goal identification and performance assessment, and potentially lead to more successful, responsive and accountable policing.


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