A Validated Framework for Measuring Interface Support for Interactive Information Seeking

In this paper we present the validation of an evaluation framework that models the support provided by search systems for different types of user and their expected types of seeking behavior. Factors determining the types of users include previous knowledge and goals. After an overview is presented, the framework is validated in two ways. First, the novel integration of the two existing information-seeking models used in the framework is validated by the correlation of multiple expert and novice analysis. Second, the framework is validated against the results produced by two separated user studies. Further, the refinements made by the first validation technique are shown to increase the accuracy of the framework through the second technique. The successful validation process has shown that the framework can identify both strong and weak areas of search interface design in only a few hours. The results produced can be used to either revise and strengthen designs or inform the structure of a user study

The intelligent browser for texpros

Browsing is a technique, which helps users to formulate their query and retrieve information in the information retrieval system. This technique provides users with capabilities of understanding their information needs and gaining system knowledge during the course of the browsing and thus it eases the users\u27 burden when issuing queries. The basic components of the browser provides an underlying structure which allows users to navigate and a browsing process controller which provides users with the needed assistance during each browsing session. In this dissertation, a new infrastructure (OP-Net), transformed from the existing object network is proposed. Each object in the object network is transformed into a predicate-augmented information repository. The predicate associated with each information repository governs the content of relevant documents in the depository during the browsing process and is updated continuously according to queries given by the user. The OP-Net with the relevant information repositories provides a dynamic and efficient environment for browsing. A new ranking model is also proposed based on the signature of the documents and the user\u27s query. The signature of a document is a document representative which utilizes the information provided by the dual model in TEXPROS (TEXt PROcessing System). With the signatures, the similarity of the document and the query can be computed, and the ranks of the documents can be derived. This dissertation describes a three-layer architecture for the browser. At the top layer, the browsing process controller conducts and monitors the browsing process, and utilizes the services provided by the service providers. At the bottom of this architecture is the storage management system which stores the documents and then associated frame instances and responses to the requests from the service providers in the second layer. This architecture supports the principle of information hiding by allowing the change of the design of each component without changing the others. In the conclusion of this dissertation, the potential improvements and future research will be proposed

Knowledge-based document retrieval with application to TEXPROS

Document retrieval in an information system is most often accomplished through keyword search. The common technique behind keyword search is indexing. The major drawback of such a search technique is its lack of effectiveness and accuracy. It is very common in a typical keyword search over the Internet to identify hundreds or even thousands of records as the potentially desired records. However, often few of them are relevant to users\u27 interests. This dissertation presents knowledge-based document retrieval architecture with application to TEXPROS. The architecture is based on a dual document model that consists of a document type hierarchy and, a folder organization. Using the knowledge collected during document filing, the search space can be narrowed down significantly. Combining the classical text-based retrieval methods with the knowledge-based retrieval can improve tremendously both search efficiency and effectiveness. With the proposed predicate-based query language, users can more precisely and accurately specify the search criteria and their knowledge about the documents to be retrieved. To assist users formulate a query, a guided search is presented as part of an intelligent user interface. Supported by an intelligent question generator, an inference engine, a question base, and a predicate-based query composer, the guided search collects the most important information known to the user to retrieve the documents that satisfy users\u27 particular interests. A knowledge-based query processing and search engine is presented as the core component in this architecture. Algorithms are developed for the search engine to effectively and efficiently retrieve the documents that match the query. Cache is introduced to speed up the process of query refinement. Theoretical proof and performance analysis are performed to prove the efficiency and effectiveness of this knowledge-based document retrieval approach

Knowledge management for TEXPROS

Most of the document processing systems today have applied Al technologies to support their system intelligent behaviors. For the application of Al technologies in such systems, the core problem is how to represent and manage different kinds of knowledge to support their inference engine components\u27 functionalities. In other words, knowledge management has become a critical issue in the document processing systems. In this dissertation, within the scope of the TEXt PROcessing System (TEXPROS), we identify knowledge of various kinds that are applicable in the system. We investigate several problems of managing this knowledge and then develop a knowledge base for TEXPROS. In developing this knowledge base, we present approaches to representing and managing different kinds of knowledge to support its inference engine components\u27 functionalities. In TEXPROS, a dual-model paradigm is used, which contains the folder organization and the document type hierarchy, to represent and manage documents. We introduce a new System Catalog structure to represent and manage the knowledge for TEXPROS. This knowledge includes the system-level information of the folder organization and the document type hierarchy, and the operational level information of the document base itself. A unified storage approach is employed to store both the operational level information and system level information. Such storage is to house the frame template base and frame instance base. An enhanced two-level thesaurus model is presented in this dissertation. When dealing with special kinds of data in processing documents, a new structure DataDomain is presented, which supports the extended thesaurus functionalities, pattern recognition and data type operations. Based on the dual-model paradigm of TEXPROS, a concept of “Semantic Range” is presented to solve the sense ambiguity problems. In this dissertation, we also present the approaches to implement the general KeyTerm transformation and approximate term matching of TEXPROS. Finally, a new component “Registration Center” at the knowledge management level of TEXPROS is presented. The registration center aims to help users handle knowledge packages for specific working domain and to solve the knowledge porting problem for TEXPROS. This dissertation is concluded with the future research work

The application of morpho-syntatic language processing to effective information retrieval

The fundamental function of an information retrieval system is to retrieve texts or documents from a database in response to a user’s request for information, such that the content of the retreived documents will be relevant to the user’s original information need. This is accomplished through matching the user’s information request against the texts in the database in order to estimate which texts are relevant. In this thesis I propose a method for using current natural language processing techniques for the construction of a text representation to be used in an information retrieval system. In order to support this proposal I have designed a matching algorithm specifically for performing the retrieval task of matching user queries against texts in a database, using the proposed text representation. Having designed this text representation and matching algorithm, I then constructed an experiment to investigate the effectiveness of the algorithm at matching phrases. This experiment involved the use of standard statistical methods to compare the phrase matching capabilities of the proposed matching algorithm to a sample of information retrieval users performing the same task. The results of this evaluation experiment allow me to comment first of all on the effectiveness of the phrase matching algorihtm that I have designed and more generally, on the usefulness of incorporating natural language processing techniques into information retrieval systems

An analytical inspection framework for evaluating the search tactics and user profiles supported by information seeking interfaces

Searching is something we do everyday both in digital and physical environments. Whether we are searching for books in a library or information on the web, search is becoming increasingly important. For many years, however, the standard for search in software has been to provide a keyword search box that has, over time, been embellished with query suggestions, Boolean operators, and interactive feedback. More recent research has focused on designing search interfaces that better support exploration and learning. Consequently, the aim of this research has been to develop a framework that can reveal to designers how well their search interfaces support different styles of searching behaviour.The primary contribution of this research has been to develop a usability evaluation method, in the form of a lightweight analytical inspection framework, that can assess both search designs and fully implemented systems. The framework, called Sii, provides three types of analyses: 1) an analysis of the amount of support the different features of a design provide; 2) an analysis of the amount of support provided for 32 known search tactics; and 3) an analysis of the amount of support provided for 16 different searcher profiles, such as those who are finding, browsing, exploring, and learning. The design of the framework was validated by six independent judges, and the results were positively correlated against the results of empirical user studies. Further, early investigations showed that Sii has a learning curve that begins at around one and a half hours, and, when using identical analysis results, different evaluators produce similar design revisions.For Search experts, building interfaces for their systems, Sii provides a Human-Computer Interaction evaluation method that addresses searcher needs rather than system optimisation. For Human-Computer Interaction experts, designing novel interfaces that provide search functions, Sii provides the opportunity to assess designs using the knowledge and theories generated by the Information Seeking community. While the research reported here is under controlled environments, future work is planned that will investigate the use of Sii by independent practitioners on their own projects

Digital disclosure in the marketspace : a case study of the REIT industry

Thesis (M.C.P.)--Massachusetts Institute of Technology, Dept. of Urban Studies and Planning, 1996.Includes bibliographical references (leaves 178-193).by Roberto Ordorica Barrera.M.C.P