This thesis builds a foundation for the philosophy of theWeb by examining the crucial question: What does a Uniform Resource Identifier (URI) mean? Does it have a sense, and can it refer to things? A philosophical and historical introduction to the Web explains the primary purpose of theWeb as a universal information space for naming and accessing information via URIs. A terminology, based on distinctions in philosophy, is employed to define precisely what is meant by information, language, representation, and reference. These terms are then employed to create a foundational ontology and principles ofWeb architecture. From this perspective, the SemanticWeb is then viewed as the application of the principles of Web architecture to knowledge representation. However, the classical philosophical problems of sense and reference that have been the source of debate within the philosophy of language return. Three main positions are inspected: the logicist position, as exemplified by the descriptivist theory of reference and the first-generation SemanticWeb, the direct reference position, as exemplified by Putnamand Kripke’s causal theory of reference and the second-generation Linked Data initiative, and a Wittgensteinian position that views the Semantic Web as yet another public language. After identifying the public language position as the most promising, a solution of using people’s everyday use of search engines as relevance feedback is proposed as a Wittgensteinian way to determine sense of URIs. This solution is then evaluated on a sample of the Semantic Web discovered by via using queries from a hypertext search engine query log. The results are evaluated and the technique of using relevance feedback from hypertext Web searches to determine relevant Semantic Web URIs in response to user queries is shown to considerably improve baseline performance. Future work for the Web that follows from our argument and experiments is detailed, and outlines of a future philosophy of the Web laid out.

Since the Web is getting bigger and bigger with a rapidly increasing number of heterogeneous Web pages, Web users often suffer from two problems: P1) irrelevant information and P2) information overload Irrelevant information indicates the weak relevance between the retrieved information and a user's information need. Information overload indicates that the retrieved information may contain 1) redundant information (e.g., common information between two retrieved Web pages) or 2) too much amount of information which cannot be easily understood by a user. We consider four major causes of those two problems P1) and P2) as follows; ??? Firstly, ambiguous query-terms. ??? Secondly, ambiguous terms in a Web page. ??? Thirdly, a query and a Web page cannot be semantically matched, because of the first and second causes. ??? Fourthly, the whole content of a Web page is a coarse context-boundary to measure the similarity between the Web page and a query. To answer those two problems P1) and P2), we consider that the meanings of words in a Web page and a query are primitive hints for understanding the related semantics of the Web page. Thus, in this dissertation, we developed three cooperative technologies: Word Sense Based Web Information Retrieval (WSBWIR), Subjective Segment Importance Model (SSIM) and Topic Focused Web Page Summarization (TFWPS). ??? WSBWIR allows for a user to 1) describe their information needs at senselevel and 2) provides one way for users to conceptually explore information existing within Web pages. ??? SSIM discovers a semantic structure of a Web page. A semantic structure respects not only Web page authors logical presentation structures but also a user specific topic interests on the Web pages at query time. ??? TFWPS dynamically generates extractive summaries respecting a user's topic interests. WSBWIR, SSIM and TFWPS technologies are implemented and experimented through several case-studies, classification and clustering tasks. Our experiments demonstrated that 1) the comparable effectiveness of exploration of Web pages using word senses, and 2) the segments partitioned by SSIM and summaries generated by TFWPS can provide more topically coherent features for classification and clustering purposes.

The search engine has become one of the most popular tools used on the Internet. Most of the existing search engines locate information based on queries consisting of a small number of keywords provided by the users. Although those search engines can query their databases and retrieve documents in a timely manner, the quality of the results is often unsatisfactory. This problem, based on previous studies and our observation, is partially due to the lack of semantic interpretation of a search request, as well as the user's incapability to precisely express their information need in a short query. In this research, we propose a conceptual framework that classifies various types of context in a Web search environment and present a new semantics-based approach that disambiguates user queries by analyzing the "relationship" context associated with query concepts.Our multi-methodological research approach includes: (i) building a context framework by categorizing different types of context; (ii) proposing a search mechanism that discovers and utilizes semantic relationships among query terms; (iii) demonstrating the practical implications of our proposed model using a proof-of-concept prototype system; and (iv) evaluating the usefulness of "relationship" context through an experimental study. From a technical perspective, our approach integrates ideas from semantic network, ontology, and information retrieval techniques. The experimental study conducted in the medical domain shows that our approach is effective and outperforms an existing popular search engine on search tasks consisting of key semantic relationships.

Since the Web is getting bigger and bigger with a rapidly increasing number of heterogeneous Web pages, Web users often suffer from two problems: P1) irrelevant information and P2) information overload Irrelevant information indicates the weak relevance between the retrieved information and a user's information need. Information overload indicates that the retrieved information may contain 1) redundant information (e.g., common information between two retrieved Web pages) or 2) too much amount of information which cannot be easily understood by a user. We consider four major causes of those two problems P1) and P2) as follows; ??? Firstly, ambiguous query-terms. ??? Secondly, ambiguous terms in a Web page. ??? Thirdly, a query and a Web page cannot be semantically matched, because of the first and second causes. ??? Fourthly, the whole content of a Web page is a coarse context-boundary to measure the similarity between the Web page and a query. To answer those two problems P1) and P2), we consider that the meanings of words in a Web page and a query are primitive hints for understanding the related semantics of the Web page. Thus, in this dissertation, we developed three cooperative technologies: Word Sense Based Web Information Retrieval (WSBWIR), Subjective Segment Importance Model (SSIM) and Topic Focused Web Page Summarization (TFWPS). ??? WSBWIR allows for a user to 1) describe their information needs at senselevel and 2) provides one way for users to conceptually explore information existing within Web pages. ??? SSIM discovers a semantic structure of a Web page. A semantic structure respects not only Web page authors logical presentation structures but also a user specific topic interests on the Web pages at query time. ??? TFWPS dynamically generates extractive summaries respecting a user's topic interests. WSBWIR, SSIM and TFWPS technologies are implemented and experimented through several case-studies, classification and clustering tasks. Our experiments demonstrated that 1) the comparable effectiveness of exploration of Web pages using word senses, and 2) the segments partitioned by SSIM and summaries generated by TFWPS can provide more topically coherent features for classification and clustering purposes.

University, Diss., 2002--Konstanz.

Web information retrieval is a relatively new research area that has attracted a significant amount of interest from researchers around the world since the emergence of the World Wide Web in the early 1990s. The problems facing successful web information retrieval are a combination of challenges that stem from traditional information retrieval and challenges characterised by the nature of the World Wide Web. The goal of any information retrieval system is to provide an information need fulfilment in response to an information need. In a web setting, this means retrieving as many relevant web documents as possible in response to an inputted query that is typically limited to only containing a few terms expressive of the user's information need. This thesis is primarily concerned with firstly reviewing pertinent literature related to various aspects of web information retrieval research and secondly proposing and investigating a novel concept and context-based approach. The approach consists of techniques that can be used together or independently and aim to provide an improvement in retrieval accuracy over other approaches. A novel concept-based term weighting technique is proposed as a new method of deriving query term significance from ontologies that can be used for the weighting of inputted queries. A technique that dynamically determines the significance of terms occurring in documents based on the matching of contexts is also proposed. Other contributions of this research include techniques for the combination of document and query term weights for the ranking of retrieved documents. All techniques were implemented and tested on benchmark data. This provides a basis for performing comparison with previous top performing web information retrieval systems. High retrieval accuracy is reported as a result of utilising the proposed approach. This is supported through comprehensive experimental evidence and favourable comparisons against previously published results.

No description available.

Thesis (M.S.)--Mississippi State University. Department of Computer Science. / Title from title screen. Includes bibliographical references.

In order to compete with the global giants, enterprises are concentrating on their core competencies and collaborating with organizations that compliment their skills and core activities. The current trend is to develop temporary alliances of independent enterprises, in which companies can come together to share skills, core competencies and resources. However, knowledge sharing and communication among multidiscipline companies is a complex and challenging problem. In a collaborative environment, the meaning of knowledge is drastically affected by the context in which it is viewed and interpreted; thus necessitating the treatment of structure as well as semantics of the data stored in enterprise repositories. Keeping the present market and technological scenario in mind, this research aims to propose tools and techniques that can enable companies to assimilate distributed information resources and achieve their business goals.

Although there is research into student learning on the Web and other computer-supported environments, there has been little investigation into the practice and pedagogy of university Web teachers. This qualitative study used a series of interviews of eight higher education faculty to gather data on their Web teaching practices, and an examination of their Web courses to identify their pedagogies. There was a notable difference in the way the four teachers with Web-assisted courses and the four teachers with Web-only courses used the Web in their teaching. Those with Web-assisted courses used the Web primarily as a connection to expanded resources and a supplement to their face-to-face teaching. Those who taught Web-only courses used the Web for resource access, and also used asynchronous dialogue and peer interactions to support student construction of knowledge. Moreover, the Web-only teachers reported a shift in their roles from lecturer and expert in the classroom to facilitator and co-learner as Web teachers. Four aspects of the Web teaching environment appear to be foundational in supporting an effective Web pedagogy: (1) the varied and extensive uses of e-mail, (2) the "think time" made possible by asynchronous dialogue, (3) distributed, hyperlinked learning, and (4) a reported shift from a content focus to process and issues because Web instructors are confident that the material is presented in the Web course as they wish it. The experiences of the Web teachers in the study would indicate that these four elements can be leveraged to improve university Web teaching and deepen student learning, perhaps even beyond results capable of achievement in face-to-face teaching. / Graduation date: 1999