The FrameNet database is being used in a variety of NLP research and applications such as word sense disambiguation, machine translation, information extraction and question answering. The database is currently available in XML format. The XML database though a wholesome way of distributing data in its entireness, is not practical for use unless converted to a more application friendly database. In light of this we have successfully converted the XML database to a relational MySQL™ database. This conversion reduced the amount of data storage amount to less than half. Most importantly the new database enables us to perform fast complex querying and facilitates use by applications and research. We show the steps taken to ensure relational integrity of the data during the refactoring process and a simple demo application demonstrating ease of use.

Finite functions (also called maps) are used to describe a number of key computations and storage mechanisms used in software and hardware interpreters. Their presence spread over various memory and speed hierarchies in hardware and through various optimization processes (algorithmic and compilation based) in software, suggests encapsulating dynamic size changes and representation optimizations in a unique abstraction to be used across traditional computation mechanisms. We developed a memory allocator for testing the finite functions. We have implemented some dynamic finite functions and performed certain experiments to see the performance speed of these finite functions. We have developed some simple but powerful application programming interfaces (API) for these finite functions.

Library information systems use different software applications and automated systems to gain access to distributed information. Rapid application development, changes made to existing software applications and development of new software on different platforms can make it difficult for library information systems to interoperate. Web services are used to offer better information access and retrieval solutions and hence make it more cost effective for libraries. This research focuses on how web services are implemented with the standard protocols like SOAP, WSDL and UDDI using different programming languages and platforms to achieve interoperability for libraries. It also shows how libraries can make use of this new technology. Since web services built on different platforms can interact with each other, libraries can access information with more efficiency and flexibility.

Machine Learning is the ability of a machine to perform better at a given task, using its previous experience. Various algorithms like decision trees, Bayesian learning, artificial neural networks and instance-based learning algorithms are used widely in machine learning systems. Current applications of machine learning include credit card fraud detection, customer service based on history of purchased products, games and many more. The application of machine learning techniques to natural language processing (NLP) has increased tremendously in recent years. Examples are handwriting recognition and speech recognition. The problem we tackle in this Problem in Lieu of Thesis is applying machine-learning techniques to improve the performance of a conversational agent. The OpenMind repository of common sense, in the form of question-answer pairs is treated as the training data for the machine learning system. WordNet is interfaced with to capture important semantic and syntactic information about the words in the sentences. Further, k-closest neighbors algorithm, an instance based learning algorithm is used to simulate a case based learning system. The resulting system is expected to be able to answer new queries with knowledge gained from the training data it was fed with.

This paper describes the general architecture and function of a Case-Based Reasoning (CBR) system implemented with ASP.NET and C#. Microsoft Visual Studio .NET and XML Web Services provide a flexible, standards-based model that allows clients to access data. Web Form Pages offer a powerful programming model for Web-enabled user interface. The system provides a variety of mechanisms and services related to story retrieval and adaptation. Users may browse and search a library of text stories. More advanced CBR capabilities were also implemented, including a multi-factor distance-calculation for matching user interests with stories in the library, recommendations on optimizing search, and adaptation of stories to match user interests.