Theoretical evaluation of XML retrieval

This thesis develops a theoretical framework to evaluate XML retrieval. XML retrieval deals with retrieving those document parts that specifically answer a query. It is concerned with using the document structure to improve the retrieval of information from documents by only delivering those parts of a document an information need is about. We define a theoretical evaluation methodology based on the idea of `aboutness' and apply it to XML retrieval models. Situation Theory is used to express the aboutness proprieties of XML retrieval models. We develop a dedicated methodology for the evaluation of XML retrieval and apply this methodology to five XML retrieval models and other XML retrieval topics such as evaluation methodologies, filters and experimental results

Theories of information and uncertainty for the modelling of information retrieval : an application of situation theory and Dempster-Shafer's theory of evidence

Current information retrieval models only offer simplistic and specific representations of information. Therefore, there is a need for the development of a new formalism able to model information retrieval systems in a more generic manner. In 1986, Van Rijsbergen suggested that such formalisms can be both appropriately and powerfully defined within a logic. The resulting formalism should capture information as it appears in an information retrieval system, and also in any of its inherent forms. The aim of this thesis is to understand the nature of information in information retrieval, and to propose a logic-based model of an information retrieval system that reflects this nature. The first objective of this thesis is to identify essential features of information in an information retrieval system. These are: 0 flow, 0 intensionality, 0 partiality, 0 structure, 0 significance, and o uncertainty. It is shown that the first four features are qualitative, whereas the last two are quantitative, and that their modelling requires different frameworks: a theory of information, and a theory of uncertainty, respectively. The second objective of this thesis is to determine the appropriate framework for each type of feature, and to develop a method to combine them in a consistent fashion. The combination is based on the Transformation Principle. Many specific attempts have been made to derive an adequate definition of information. The one adopted in this thesis is based on that of Dretske, Barwise, and Devlin who claimed that there is a primitive notion of information in terms of which a logic can be defined, and subsequently developed a theory of information, namely Situation Theory. Their approach was in accordance with Van Rijsbergen' s suggestion of a logic-based formalism for modelling an information retrieval system. This thesis shows that Situation Theory is best at representing all the qualitative features. Regarding the modelling of the quantitative features of information, this thesis shows that the framework that models them best is the Dempster-Shafer Theory of Evidence, together with the notion of refinement, later introduced by Shafer. The third objective of this thesis is to develop a model of an information retrieval system based on Situation Theory and the Dempster-Shafer Theory of Evidence. This is done in two steps. First, the unstructured model is defined in which the structure and the significance of information are not accounted for. Second, the unstructured model is extended into the structured model, which incorporates the structure and the significance of information. This strategy is adopted because it enables the careful representation of the flow of information to be performed first. The final objective of the thesis is to implement the model and to perform empirical evaluation to assess its validity. The unstructured and the structured models are implemented based on an existing on-line thesaurus, known as WordNet. The experiments performed to evaluate the two models use the National Physical Laboratory standard test collection. The experimental performance obtained was poor, because it was difficult to extract the flow of information from the document set. This was mainly due to the data used in the experimentation which was inappropriate for the test collection. However, this thesis shows that if more appropriate data, for example, indexing tools and thesauri, were available, better performances would be obtained. The conclusion of this work was that Situation Theory, combined with the Dempster-Shafer Theory of Evidence, allows the appropriate and powerful representation of several essential features of information in an information retrieval system. Although its implementation presents some difficulties, the model is the first of its kind to capture, in a general manner, these features within a uniform framework. As a result, it can be easily generalized to many types of information retrieval systems (e.g., interactive, multimedia systems), or many aspects of the retrieval process (e.g., user modelling)

Lost Luggage: A Field Study of Emotion-Antecedent Appraisal

One hundred twelve airline passengers reporting their luggage lost to the baggage retrieval service in a major international airport were interviewed after their interaction with an airline agent. Participants were asked to rate their emotional state before and after the interaction with the agent and to provide information on how they had appraised the situation. The data are interpreted with respect to (1) type and intensity of the emotions felt in this situation, (2) appraisal theory predictions of emotion elicitation and differentiation, and (3) emotional change in the course of the interaction following reappraisal of the situatio

Retrieval Inhibition In Human Memory: An Extension And Evaluation Of The Sam Theory

Retrieval inhibition occurs when related information presented during the act of remembering inhibits recall performance. In the part-list cuing paradigm, subjects are presented with part of a list and asked to recall the rest of the list. A comparison with an uncued condition shows that recall is reduced by the part-list cues. This finding is important because many memory theories propose that lists of words are learned by forming associations between the words and, thus, part-list cues should allow subjects to follow these associations and increase their recall. Shiffrin\u27s SAM (Search of Associative Memory) theory of memory retrieval provides the most promising explanation for the part-list curing effect. The purpose of the present research was to apply the SAM theory to two new retrieval inhibition situations and evaluate its performance. In Experiments 1 and 2 it was shown that part-list cues that are delayed for short periods (15 or 30 seconds) inhibit written recall, while cues delayed for long periods (1, 2, or 4 minutes) have no effect. A computer simulation program based on the SAM theory was able to model the correct effects of delayed cues in this situation. In Experiment 3 the effects of delayed part-list cues were examined under verbal recall conditions and it was found that cues delayed for long periods (3 minutes) facilitated recall performance. However, the SAM simulation program was not able to model the effects of delayed cues in this situation. In a fourth experiment the sampling rule in the SAM theory was evaluated. The SAM theory predicts that strong items in memory should block the recall of weaker items. Experiment 4 showed that the blocking effect produced by strong items is quite small, but the SAM simulation program modelled the correct amount of blocking. Thus, the present research provided important new evidence on the effects of part-list cues and the competition action of items in memory. Further, the SAM theory of memory retrieval was able to model most of the data, although some important problems with the theory were discovered

Enhancing Student\u27s Critical Thinking Skills Throughout the Curriculum Through the Use of Applied Critical Thinking

Using elements of Bloom\u27s Taxonomy, Critical Thinking, and Scientific Research theory, Embry-Riddle Extended Campus adult learners can be taught how to become more effective critical thinkers by studying the elements of critical thinking necessary to succeed in each course they take. As the specific situational demands for academic success in each course dictate, these adult learners learn to first succeed in identifying the critical thinking elements in each course, then in the overall academic discipline of each course, and, eventually, in each professional and personal life situation they become involved in. Relying on the critical thinking skills necessary to succeed in information retrieval using online technology and finding solutions to problems through database searching and WWW search engines, adult learners can effectively become critical thinkers and information finders. It was concluded that Bloom\u27s Taxonomy is an appropriate educational critical thinking guideline, and that extended campuses should create and support critical thinking across the curriculum programs. It was recommended that critical thinking across the curriculum and information retrieval skills be adopted by ERAU\u27s Extended Campus as syllabus learning outcomes for all courses

NewsView: A Recommender System for Usenet based on FAST Data Search

This thesis combines aspects from two approaches to information access, information filtering and information retrieval, in an effort to improve the signal to noise ratio in interfaces to conversational data. These two ideas are blended into one system by augmenting a search engine indexing Usenet messages with concepts and ideas from recommender systems theory. My aim is to achieve a situation where the overall result relevance is improved by exploiting the qualities of both approaches. Important issues in this context are obtaining ratings, evaluating relevance rankings and the application of useful user profiles. An architecture called NewsView has been designed as part of the work on this thesis. NewsView describes a framework for interfaces to Usenet with information retrieval and information filtering concepts built into it, as well as extensive navigational possibilities within the data. My aim with this framework is to provide a testbed for user interface, information filtering and information retrieval issues, and, most importantly, combinations of the three

Navigating Monsters: Credibility in the Twittersphere

The increasing use of OSM during emergency, or potentially threatening, situations creates conditions in which emergency planners and responders need a high level of investigative skill to weed through a dynamic information landscape to determine the quality of information to contribute to improved situation awareness. This weeding process transforms the big data environment of OSM to focused information retrieval. Inquiry into indicators of quality in OSM (authority, objectivity, currency, coverage, and glyphicality) during severe weather situations informs how OSM impacts the information behavior of the severe weather enterprise of the U. S. Specifically, this paper focuses on investigation into how a particular element of the severe weather enterprise in the Midwest, the integrated warning team (IWT), identifies relevant information in OSM during severe weather events. This paper describes the theoretical framework of an inquiry into information behavior of the IWT during severe weather events through the lens of cognitive authority theory (Wilson, 1983) and Bonnici’s (2016) CAF-QIS for understanding the phenomena of both credibility and trustworthiness in the Twittersphere where author is potentially unknown

A framework for investigating the interaction in information retrieval

To increase retrieval effectiveness, information retrieval systems must offer better supports to users in their information seeking activities. To achieve this, one major concern is to obtain a better understanding of the nature of the interaction between a user and an information retrieval system. For this, we need a means to analyse the interaction in information retrieval, so as to compare the interaction processes within and across information retrieval systems. We present a framework for investigating the interaction between users and information retrieval systems. The framework is based on channel theory, a theory of information and its flow, which provides an explicit ontology that can be used to represent any aspect of the interaction process. The developed framework allows for the investigation of the interaction in information retrieval at the desired level of abstraction. We use the framework to investigate the interaction in relevance feedback and standard web search