Improving Retrieval of Information from the Internet

To improve the quality of the search result returned by the internet which makes users have to look through a huge amount of links for the real answers, we utilized the high quality links Google produces and the Information Retrieval technology to implement a Question Answering (QA) system. This system analyzes and downloads the text contents from the relevant web pages Google searches based on the users\u27 questions to build a dynamic knowledge collection; retrieves the relevant passages from the collection and sends the ranked passages back. The users can further refine their questions in the query refinement step for the better answers. A novel search strategy was designed to detect the semantic connections between the question and the documents. This answer retrieval also involves the TF-IDF algorithm and Vector Space Model for the document indexing. We have modified the original Cosine Coefficient Similarity Measurement to rank the candidate answers

Using the organizational and narrative thread structures in an e-book to support comprehension.

Stories, themes, concepts and references are organized structurally and purposefully in most books. A person reading a book needs to understand themes and concepts within the context. Schanks Dynamic Memory theory suggested that building on existing memory structures is essential to cognition and learning. Pirolli and Card emphasized the need to provide people with an independent and improved ability to access and understand information in their information seeking activities. Through a review of users reading behaviours and of existing e-Book user interfaces, we found that current e-Book browsers provide minimal support for comprehending the content of large and complex books. Readers of an e-Book need user interfaces that present and relate the organizational and narrative structures, and moreover, reveal the thematic structures. This thesis addresses the problem of providing readers with effective scaffolding of multiple structures of an e-Book in the user interface to support reading for comprehension. Recognising a story or topic as the basic unit in a book, we developed novel story segmentation techniques for discovering narrative segments, and adapted story linking techniques for linking narrative threads in semi-structured linear texts of an e-Book. We then designed an e-Book user interface to present the complex structures of the e-Book, as well as to assist the reader to discover these structures. We designed and developed evaluation methodologies to investigate reading and comprehension in e-Books, in order to assess the effectiveness of this user interface. We designed semi-directed reading tasks using a Story-Theme Map, and a set of corresponding measurements for the answers. We conducted user evaluations with book readers. Participants were asked to read stories, to browse and link related stories, and to identify major themes of stories in an e-Book. This thesis reports the experimental design and results in detail. The results confirmed that the e-Book interface helped readers perform reading tasks more effectively. The most important and interesting finding is that the interface proved to be more helpful to novice readers who had little background knowledge of the book. In addition, each component that supported the user interface was evaluated separately in a laboratory setting and, these results too are reported in the thesis

Case based design of knitwear

In the developed world we are surrounded by man-made objects, but most people give little thought to the complex processes needed for their design. The design of hand knitting is complex because much of the domain knowledge is tacit. The objective of this thesis is to devise a methodology to help designers to work within design constraints, whilst facilitating creativity. A hybrid solution including computer aided design (CAD) and case based reasoning (CBR) is proposed. The CAD system creates designs using domain-specific rules and these designs are employed for initial seeding of the case base and the management of constraints. CBR reuses the designer's previous experience. The key aspects in the CBR system are measuring the similarity of cases and adapting past solutions to the current problem. Similarity is measured by asking the user to rank the importance of features; the ranks are then used to calculate weights for an algorithm which compares the specifications of designs. A novel adaptation operator called rule difference replay (RDR) is created. When the specifications to a new design is presented, the CAD program uses it to construct a design constituting an approximate solution. The most similar design from the case-base is then retrieved and RDR replays the changes previously made to the retrieved design on the new solution. A measure of solution similarity that can validate subjective success scores is created. Specification similarity can be used as a guide whether to invoke CBR, in a hybrid CAD-CBR system. If the newly resulted design is suffciently similar to a previous design, then CBR is invoked; otherwise CAD is used. The application of RDR to knitwear design has demonstrated the flexibility to overcome deficiencies in rules that try to automate creativity, and has the potential to be applied to other domains such as interior design

Fourth Conference on Artificial Intelligence for Space Applications

Proceedings of a conference held in Huntsville, Alabama, on November 15-16, 1988. The Fourth Conference on Artificial Intelligence for Space Applications brings together diverse technical and scientific work in order to help those who employ AI methods in space applications to identify common goals and to address issues of general interest in the AI community. Topics include the following: space applications of expert systems in fault diagnostics, in telemetry monitoring and data collection, in design and systems integration; and in planning and scheduling; knowledge representation, capture, verification, and management; robotics and vision; adaptive learning; and automatic programming

Advances in Robot Navigation

Robot navigation includes different interrelated activities such as perception - obtaining and interpreting sensory information; exploration - the strategy that guides the robot to select the next direction to go; mapping - the construction of a spatial representation by using the sensory information perceived; localization - the strategy to estimate the robot position within the spatial map; path planning - the strategy to find a path towards a goal location being optimal or not; and path execution, where motor actions are determined and adapted to environmental changes. This book integrates results from the research work of authors all over the world, addressing the abovementioned activities and analyzing the critical implications of dealing with dynamic environments. Different solutions providing adaptive navigation are taken from nature inspiration, and diverse applications are described in the context of an important field of study: social robotics