Machine Learning and the Cognitive Basis of Natural Language

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Back to the Future: Logic and Machine Learning

In this paper we argue that since the beginning of the natural language processing or computational linguistics there has been a strong connection between logic and machine learning. First of all, there is something logical about language or linguistic about logic. Secondly, we argue that rather than distinguishing between logic and machine learning, a more useful distinction is between top-down approaches and data-driven approaches. Examining some recent approaches in deep learning we argue that they incorporate both properties and this is the reason for their very successful adoption to solve several problems within language technology

Reading in Web-based hypertexts: cognitive processes strategies and reading goals

Hypertext is a multi-linear electronic, textual and interactive environment to present information. The objective of such an environment is that readers may browse through linked, cross-referenced, annotated texts in a multi-sequential manner, and thus, it is believed, to improve the learning. However, early and current research findings have revealed some mixed results concerning the alleged advantage of hypertext on learning over paper-based documents. Researchers have identified the lack of research about the cognitive processes and the strategies that readers use during reading as one of the main factors for such results. As a result, there is a need and scope for further research in modelling the cognitive processes involved in reading comprehension and the reading strategies in a hypertext environment. This research addresses some of the gaps in the field by proposing a model that represents the sequence of events that take place during reading in a Web-based hypertext environment. Also, emphasis is placed on the strategies that readers use during hypertext reading and on the potential effect of different reading goals on reading comprehension. The evaluation of the model and the other hypotheses is conducted in two experiments using qualitative and quantitative methods. The first experiment employs the think aloud method. Forty two subjects participated. The results demonstrated that the proposed model precisely describes the sequence of events that take place during hypertext reading. They did not reveal any significant difference between different reading goals and understanding. They revealed four reading strategies: serial, serial overview, mixed, and mixed overview, and they identified three factors that influence the selection of hyperlinks: coherence, link location, and personal interest. The second experiment is an independent samples design experiment with ninety subjects. The results confirmed those found in the first experiment. The current study makes a contribution in the field of hypertext reading by proposing and evaluating a procedural model and by making this model graphic. By doing so it addresses some of the voids in the field, expands our understanding of the reading processes and the reading strategies, and provides practical guideliness which are enhanced to promote design supporting effective learning processes

Reading in Web-based hypertexts : cognitive processes strategies and reading goals

Hypertext is a multi-linear electronic, textual and interactive environment to present information. The objective of such an environment is that readers may browse through linked, cross-referenced, annotated texts in a multi-sequential manner, and thus, it is believed, to improve the learning. However, early and current research findings have revealed some mixed results concerning the alleged advantage of hypertext on learning over paper-based documents. Researchers have identified the lack of research about the cognitive processes and the strategies that readers use during reading as one of the main factors for such results. As a result, there is a need and scope for further research in modelling the cognitive processes involved in reading comprehension and the reading strategies in a hypertext environment. This research addresses some of the gaps in the field by proposing a model that represents the sequence of events that take place during reading in a Web-based hypertext environment. Also, emphasis is placed on the strategies that readers use during hypertext reading and on the potential effect of different reading goals on reading comprehension. The evaluation of the model and the other hypotheses is conducted in two experiments using qualitative and quantitative methods. The first experiment employs the think aloud method. Forty two subjects participated. The results demonstrated that the proposed model precisely describes the sequence of events that take place during hypertext reading. They did not reveal any significant difference between different reading goals and understanding. They revealed four reading strategies: serial, serial overview, mixed, and mixed overview, and they identified three factors that influence the selection of hyperlinks: coherence, link location, and personal interest. The second experiment is an independent samples design experiment with ninety subjects. The results confirmed those found in the first experiment. The current study makes a contribution in the field of hypertext reading by proposing and evaluating a procedural model and by making this model graphic. By doing so it addresses some of the voids in the field, expands our understanding of the reading processes and the reading strategies, and provides practical guideliness which are enhanced to promote design supporting effective learning processes.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Learning theories from text

In this paper we describe a method of automatically learning domain theories from parsed corpora of sentences from the relevant domain and use FSA techniques for the graphical representation of such a theory. By a ‘domain theory ’ we mean a collection of facts and generalisations or rules which capture what commonly happens (or does not happen) in some domain of interest. As language users, we implicitly draw on such theories in various disambiguation tasks, such as anaphora resolution and prepositional phrase attachment, and formal encodings of domain theories can be used for this purpose in natural language processing. They may also be objects of interest in their own right, that is, as the output of a knowledge discovery process. The approach is generizable to different domains provided it is possible to get logical forms for the text in the domain.