Data‐driven approaches to information access

This paper summarizes three lines of research that are motivated by the practical problem of helping users find information from external data sources, most notably computers. The application areas include information retrieval, text categorization, and question answering. A common theme in these applications is that practical information access problems can be solved by analyzing the statistical properties of words in large volumes of real world texts. The same statistical properties constrain human performance, thus we believe that solutions to practical information access problems can shed light on human knowledge representation and reasoning.     

Automatic question generation and answer assessment for subjective examination

Automatic generation of questions and evaluating their answers is a highly challenging task in natural language processing and educational technology. This work focuses on generating subjective questions and also an evaluation system is suggested for assessing the answers. For generating the questionnaires, key-phrases are extracted from the course curriculum (syllabus). Next, based on the key-phrases, different types of subjective questions are generated. Finally, the evaluation of student’s responses is achieved using a multi-criteria-decision-making approach. It uses a set of model answers taken from different textbooks and subject experts to evaluate the answers. Multiple measures are used to assess the answers by comparing them with this model set. The results of the profound system reveal that the automated appraisal process can reduce the manual effort of the human.     

The effects of local and global processing orientation on eyewitness identification performance

Recent work has demonstrated that performance on a simultaneous target-present photographic line-up can be enhanced by prior global processing orientation, and hindered by prior local processing orientation induced by processing Navon letter stimuli. A series of studies explore the generality of this processing bias effect using either videotaped scenarios or live interactions. Five experiments demonstrate that these effects are seen across a range of test stimuli, test formats, and test instructions. These data inform the processes engaged in by witnesses when making line-up identifications and indicate that it may be possible to improve the accuracy of witnesses making such judgements.     

Design and implementation of domain-specific cognitive system based on question similarity algorithm

The cognitive system is an artificial intelligence product that integrates natural language processing techniques. The biggest d on logical reasoning, which can help users improve exploration and accelerate discovery. On the basis of natural language processing and logical reasoning, the paper adopts similarity algorithm bas difference between big data analysis systems and cognitive systems is that cognitive systems can directly deal with the problems raised by natural language forms and provide predictions baseded on question sentences, designs a cognitive system for specific domains, and finally realizes it on the NAO robot platform.     

Institutional Insights for Analysing Strategic Manoeuvring in the British Prime Minister’s Question Time

This paper aims at creating an adequate theoretical basis for a systematic integration of institutional insights into the pragma-dialectical analysis of argumentative exchanges that occur in institutionalised contexts. The argumentative practice of Prime Minister’s Question Time in the British House of Commons is examined, as a case in point, in order to illustrate how the knowledge of the characteristics of an institution, its rules and conventions can be integrated into the pragma-dialectical analysis. The paper highlights the role that theoretical concepts and tools such as strategic manoeuvring, argumentative activity types and dialectical profiles play in this integration.

Answer comparison in automated question answering

In the context of Question Answering (QA) on free text, we assess the value of answer comparison and information fusion in handling multiple answers. We report improvements in answer re-ranking using fusion on a set of location questions and show the advantages of considering candidates as allies rather than competitors. We conclude with some observations about answer modeling and evaluation methodology, arising from a more recent experiment with a larger set of questions and a greater diversity of question types and candidates.     

Using logical relevance for question answering

We propose a novel method of determining the appropriateness of an answer to a question through a proof of logical relevance rather than a logical proof of truth. We define logical relevance as the idea that answers should not be considered as absolutely true or false in relation to a question, but should be considered true more flexibly in a sliding scale of aptness. This enables us to reason rigorously about the appropriateness of an answer even in cases where the sources we are getting answers from are incomplete or inconsistent or contain errors. We show how logical relevance can be implemented through the use of measured simplification, a form of constraint relaxation, in order to seek a logical proof than an answer is in fact an answer to a particular question. We then give an example of such an implementation providing a set of specific rules for this purpose.     

The fallacy of fallacies

Several of the so-called fallacies in Aristotle are not in fact mistaken inference-types, but mistakes or breaches of rules in the questioning games which were practiced in the Academy and in the Lyceum. Hence the entire Aristotelian theory of fallacies ought to be studied by reference to the author's interrogative model of inquiry, based on his theory of questions and answers, rather than as a part of the theory of inference. Most of the fallacies mentioned by Aristotle can in fact be diagnosed by means of the interrogative model, including petitio principii, multiple questions, babbling, etc., and so can Aristotle's alleged anticipation of the fallacy of argumentum ad hominem. The entire Aristotelian conception of inquiry is an interrogative one. Deductive conclusions caught Aristotle's attention in the form of answers that every rational interlocutor must give, assuming only his own earlier answers. Several features of Aristotle's methodology can be understood by means of the interrogative model, including the role of endoxa in it. Theoretically, there is also considerable leeway as to whether fallacies are conceived of as mistakes in questioning or as breaches of the rules that govern questioning games.     

Cogex: A semantically and contextually enriched logic prover for question answering

This paper presents the architecture and functionality of a logic prover designed for question answering. The approach transforms questions and answer passages into logic representations based on syntactic, semantic and contextual information. World knowledge supplements the linguistic, ontological, and temporal axioms supplied to the prover which renders a deep understanding of the relationship between the question and answer text. The trace of the proofs provides a basis for generating human comprehensible answer justifications. The results show that the prover boosts the performance of the Question Answering system on TREC 2004 questions by 12%.