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Using an Ontology to Automatically Generate Questions for the Determination of Situations
Abstract
We investigate whether the automatic generation of questions from an ontology leads to a trustworthy determination of a situation.
With our Situation Awareness Question Generator (SAQG) we automatically generate questions from an ontology. The experiment
shows that people with no previous experience can characterize hectic situations rather fast and trustworthy. When humans
are participating as a sensor to gather information it is important to use basic concepts of perception and thought.
... An essential part of any organization's anti-phishing strategy is to take a proactive stance by educating employees to identify phishing emails and report them [28]. One intervention that educates employees is the execution of phishing training simulations during which the organizations IT security department recreates phishing scenarios by sending out artificial phishing emails to employees [32]. Instead of visiting a malicious website the employee that clicks on the link in the email is redirected to a notification page with a message informing the employee that he or she took part in a phishing simulation. ...
... Teisma et al. [18] developed Situation Awareness Question Generator (SAQG) for generating questions from ontology. SAQG is used to determine the situation and to generate yes-no type questions. ...
... This chapter is based on a paper presented at DEXA 2011: 22nd International Conference on Database and Expert Systems Applications (Teitsma et al., 2011b). The paper is extended with an elaboration of the analysis and results. ...
... This situation is then communicated to the server. Previous experiments showed that questions generated from an ontology created by knowledge engineers (an expert-based ontology) did not lead to thrustworthy answers while questions generated from a ontology based on pragmatic considerations (a pragmatic-based ontology) were suitable to determine a situation [6,5]. ...
In this paper we present an experiment which has been performed to validate a pragmatic-based, expert-based and basic-level ontology. These ontologies were created for use in an application which generates questions for ordinary people with the purpose to determine a crisis situation. All three ontologies have specific characteristics related to their method of creation. This experiment shows that using the basic-level ontology results in the fastest and least ambiguous determination of a crisis situation.
... In another application, Teitsma et al. [22] presented an ontology-based generation approach for situation determination. A traffic accident ontology and two databases on accidents were used to: (i) generate questions from infons (sets of field values describing the situation; such as weather or injuries) and (ii) get validation answers from human observers who watched video scenes describing the target situations. ...
Background
The increasing number of open-access ontologies and their key role in several applications such as decision-support systems highlight the importance of their validation. Human expertise is crucial for the validation of ontologies from a domain point-of-view. However, the growing number of ontologies and their fast evolution over time make manual validation challenging. Methods
We propose a novel semi-automatic approach based on the generation of natural language (NL) questions to support the validation of ontologies and their evolution. The proposed approach includes the automatic generation, factorization and ordering of NL questions from medical ontologies. The final validation and correction is performed by submitting these questions to domain experts and automatically analyzing their feedback. We also propose a second approach for the validation of mappings impacted by ontology changes. The method exploits the context of the changes to propose correction alternatives presented as Multiple Choice Questions. ResultsThis research provides a question optimization strategy to maximize the validation of ontology entities with a reduced number of questions. We evaluate our approach for the validation of three medical ontologies. We also evaluate the feasibility and efficiency of our mappings validation approach in the context of ontology evolution. These experiments are performed with different versions of SNOMED-CT and ICD9. Conclusions
The obtained experimental results suggest the feasibility and adequacy of our approach to support the validation of interconnected and evolving ontologies. Results also suggest that taking into account RDFS and OWL entailment helps reducing the number of questions and validation time. The application of our approach to validate mapping evolution also shows the difficulty of adapting mapping evolution over time and highlights the importance of semi-automatic validation.
... Professional workers use concepts which are less detailed than the concepts domain experts use. With this ontology we generated questions that were answered in a more valid way than the questions generated in the previous experiment (Teitsma et al., 2011b). However, these studies focused on the automatic generation of questions and the evaluation of the appropriateness of the answers provided. ...
Using an ontology to automatically generate questions for ordinary people requires a structure and concepts compliant with human thought. Here we present methods to develop a pragmatic, expert-based and a basic-level ontology and a framework to evaluate these ontologies. Comparing these ontologies shows that expert-based ontologies are most easy to construct but lack required cognitive semantic characteristics. Basic-level ontologies have structure and concepts which are better in terms of cognitive semantics but are most expensive to construct.
... The use of the semantic web to generate questions has been studied at length [1][2] [3][8] [9]. Indeed, domain ontologies can be considered a proper formalism as the basis for automatic generation of MCQs. ...
In this paper, we present a methodology to generate diagrammatical multiple choice questions from a knowledge base. When considering a knowledge base, the main strategies discussed in the literature are class-based, property-based and terminology-based, and the generated multiple choice questions are typical with all the choices (correct answer and distractors) being of atomic types such as plain text. In this paper, we introduce graph-based strategies, enabling the generation of choices (correct answer and distractors) in the form of complex structures such as diagrams, and discuss different approaches to take into account difficulty levels when generating the questions.
A problem of evolvability is widely discussed in the current world, and still, it has not been fully addressed yet. Our approach tries to improve evolvability in a domain of documents. Our approach is based on principles and recommendations from the Normalized Systems Theory. We try to redefine the process of how the document is created and maintained by involving ontologies. We offer a solution which should increase evolvability for a sort of documents which is created by a template and which is often updated. We demonstrate our solution to an example of a Data Management Plan document.
Categorizations which humans make of the concrete world are not arbitrary but highly determined. In taxonomies of concrete objects, there is one level of abstraction at which the most basic category cuts are made. Basic categories are those which carry the most information, possess the highest category cue validity, and are, thus, the most differentiated from one another. The four experiments of Part I define basic objects by demonstrating that in taxonomies of common concrete nouns in English based on class inclusion, basic objects are the most inclusive categories whose members: (a) possess significant numbers of attributes in common, (b) have motor programs which are similar to one another, (c) have similar shapes, and (d) can be identified from averaged shapes of members of the class. The eight experiments of Part II explore implications of the structure of categories. Basic objects are shown to be the most inclusive categories for which a concrete image of the category as a whole can be formed, to be the first categorizations made during perception of the environment, to be the earliest categories sorted and earliest named by children, and to be the categories most codable, most coded, and most necessary in language.
Past and future objectives remain the same in crises, providing relevant communities collaborative knowledge systems to exchange information.
Ontology is defined as an explicit formal specification of a shared conceptualization. It can provide semantic meaning through relations between concepts. As a fine model for presenting hierarchy and semantic meaning of concepts, Ontology is widely concerned and extensively applied to many fields. This paper probes into the construction method, processes and key points of the ontologization of traffic accidents by analyzing the needs of traffic accident ontology. Finally it presents an ontology-based prototype framework of traffic accidents management system from the hierarchical structured point of view.
This paper introduces the concept of participatory risk management (PRM). By involving community members and netizens in the risk management process we believe the community will become safer and participants will become smarter in dealing with risks. A PRM gaming system concept for incentivizing community risk management through rewarding play is presented as an example application of PRM.
The notions of “situation” and “situation awareness” have been formulated by many authors in various contexts. In this paper, we present a formalization of situations that is compatible with the interpretation of situation awareness in terms of human awareness as well as the situation theory of Barwise and Devlin. The purpose of this paper is to capture the situation theory of Barwise in terms of an OWL ontology. This allows one to express situations in a commonly supported language with computer processable semantics. The paper provides a description of the classes and the properties in the ontology, and illustrates the formalization with some simple examples.
The proposition that event taxonomies have a “basic” level was tested. In the first two tasks of the experiment, taxonomically
related event categories were elicited. Nine taxonomies were constructed from subjects’ responses on these tasks. In the third
task, subjects listed attributes for events categories from the three levels of abstraction of these taxonomies. A single,
common level of abstraction (the basic level) was identified. Subjects listed significantly more attributes for basic categories
than for superordinate categories, but not significantly more attributes for the lower, subordinate-level categories. Further
analyses showed that basic and subordinate categories elicited a greater number of concrete and event-related features than
action and personrelated features, and that superordinate categories showed the opposite trend. These findings are discussed
in terms of general principles of categorization applied to events, objects, and scenes, and the particular characteristics
of events.
In this paper, we present a conceptual framework for indexing different aspects of visual information. Our framework unifies concepts from the literature in diverse fields such as cognitive psychology, library sciences, art, and the more recent contentbased retrieval. We present multiple level structures for visual and non-visual information. The ten-level visual structure presented provides a systematic way of indexing images based on syntax (e.g., color, texture, etc.) and semantics (e.g., objects, events, etc.), and includes distinctions between general concept and visual concept. We define different types of relations (e.g., syntactic, semantic) at different levels of the visual structure, and also use a semantic information table to summarize important aspects related to an image. While the focus is on the development of a conceptual indexing structure, our aim is also to bring together the knowledge from various fields, unifying the issues that should be considered when building ...
Community database on accidents on the roads in europe
- E U Commission
Situation awareness. NSF, High-Confidence Software Platforms for Cyber-Physical Systems
- U Ramachandran