Data Mining Practical Machine Learning Tools and Techniques

How to Do Things With Words

https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1551-6709.2010.01106.x

Composition in distributional models of semantics.

https://dspace.stir.ac.uk/bitstream/1893/25490/1/affective-computing-review.pdf

A review of affective computing

The major change in the second edition of this book is the addition of a new chapter on probabilistic retrieval. This chapter has been included because I think this is one of the most interesting and active areas of research in information retrieval. There are still many problems to be solved so I hope that this particular chapter will be of some help to those who want to advance the state of knowledge in this area. All the other chapters have been updated by including some of the more recent work on the topics covered. In preparing this new edition I have benefited from discussions with Bruce Croft, The material of this book is aimed at advanced undergraduate information (or computer) science students, postgraduate library science students, and research workers in the field of IR. Some of the chapters, particularly Chapter 6 * , make simple use of a little advanced mathematics. However, the necessary mathematical tools can be easily mastered from numerous mathematical texts that now exist and, in any case, references have been given where the mathematics occur. I had to face the problem of balancing clarity of exposition with density of references. I was tempted to give large numbers of references but was afraid they would have destroyed the continuity of the text. I have tried to steer a middle course and not compete with the Annual Review of Information Science and Technology. Normally one is encouraged to cite only works that have been published in some readily accessible form, such as a book or periodical. Unfortunately, much of the interesting work in IR is contained in technical reports and Ph.D. theses. For example, most the work done on the SMART system at Cornell is available only in reports. Luckily many of these are now available through the National Technical Information Service (U.S.) and University Microfilms (U.K.). I have not avoided using these sources although if the same material is accessible more readily in some other form I have given it preference. I should like to acknowledge my considerable debt to many people and institutions that have helped me. Let me say first that they are responsible for many of the ideas in this book but that only I wish to be held responsible. My greatest debt is to Karen Sparck Jones who taught me to research information retrieval as an experimental science. Nick Jardine and Robin …

Information retrieval

This paper is concerned with the design of a novel approach for constructing Conversational Agents (CA) using sentence similarity measures. Most CA's scripts are organized into contexts consisting of a number of hierarchically organized rules. Each rule possesses a list of structural patterns of sentences and an associated response. User input is then matched against the patterns and the pre-determined response is sent as output. The huge overhead and maintenance of these CAs undoubtedly suggest scope for alternative approaches. In the proposed approach, sentence similarity measures are employed to examine scripts consisting of natural language sentences. This CA will be evaluated against an existing pattern-scripted CA using a set of domain-specific user utterances. Results indicate a substantial reduction of the proposed CA's knowledge-base and, thus, overall maintenance.

/pdf/a-novel-approach-for-constructing-conversational-agents-3h2oi1ysmd.pdf

A Novel Approach for Constructing Conversational Agents using Sentence Similarity Measures

In the UK, several laws and regulations exist to protect employees from harassment. Organisations operating in the UK create comprehensive and carefully-worded bullying and harassment policies and procedures to cover the key aspects of each regulation. In large organisations, such policies often result in a high support cost, including specialist training for the management team and human resources (HR) advisors. This paper presents a novel conversational expert system which supports bullying and harassment policies in large organisations. Information about the bullying and harassment policies and their application within organisations was acquired using knowledge engineering techniques. A knowledge tree is used to represent the knowledge intuitively, and a dynamic graphical user interface (GUI) is proposed to enable the knowledge to be traversed graphically. Adam is a conversational agent allowing users to type in questions in natural language at any point and receive a simple and direct answer. An independent evaluation of the system has given promising results.

A conversational expert system supporting bullying and harassment policies

This paper presents a novel technique for the classification of Arabic sentences as Dialogue Acts, based on structural information contained in Arabic function words. It focuses on classifying questions and non-questions utterances as they are used in Conversational Agents. The proposed technique extracts function words features by replacing them with numeric tokens and replacing each content word with a standard numeric token. The Decision Tree has been chosen for this work to extract the classification rules. Experiments provide evidence for highly effective classification. The extracted classification rules will be embedded into a Conversational Agent called ArabChat in order to classify Arabic utterances before further processing on these utterances. This paper presents a complement work for the ArabChat to improve its performance by differentiating among question-based and non question-based utterances.

User's utterance classification using machine learning for Arabic Conversational Agents

Goal-orientated Conversational Agents are a specific family of conversational agents that are designed to converse with humans through the use of natural language dialogue to achieve a specific task. Traditionally, they utilise pattern matching algorithms to capture the values of specific attributes through their values through dialogue interaction with a user. This is achieved through the use of scripts which contain sets of rules about the domain and a knowledge base to guide the conversation towards achieving a specific goal. Such systems are ideal for providing clear and consistent advice 24 hours a day in many different scenarios, including advising employees about their organisations policies and procedures, guiding a user through buying a suitable product, and tutoring a student to understand a learning objective. This paper presents an overview of a methodology for constructing goal orientated conversational agents. Three case studies which employ this methodology are introduced and evaluated.

/pdf/goal-orientated-conversational-agents-applications-to-13gb9g78gb.pdf

Goal orientated conversational agents: applications to benefit society

Semantic similarity is an essential component of numerous applications in fields such as natural language processing, artificial intelligence, linguistics, and psychology. Most of the reported work has been done in English. To the best of our knowledge, there is no word similarity measure developed specifically for Arabic. This paper presents a method to measure the semantic similarity between two Arabic words in the Arabic knowledge base. The semantic similarity is calculated through the combination of the common and different attributes between the Arabic words in the hierarchy semantic net. We use a previously developed Arabic word benchmark dataset to optimize and evaluate the Arabic measure. Experimental evaluation indicates that the Arabic measure is performing well. It has achieved a correlation value of 0.894 compared with the average value of human participants of 0.893 on evaluation dataset.

Zuhair Bandar

Papers

A Novel Approach for Constructing Conversational Agents using Sentence Similarity Measures

A conversational expert system supporting bullying and harassment policies

User's utterance classification using machine learning for Arabic Conversational Agents

Goal orientated conversational agents: applications to benefit society

AWSS: An Algorithm for Measuring Arabic Word Semantic Similarity