Fitting aggregation operators to data

Theoretical advances in modelling aggregation of information produced a wide range of aggregation operators, applicable to almost every practical problem. The most important classes of aggregation operators include triangular norms, uninorms, generalised means and OWA operators.With such a variety, an important practical problem has emerged: how to fit the parameters/ weights of these families of aggregation operators to observed data? How to estimate quantitatively whether a given class of operators is suitable as a model in a given practical setting? Aggregation operators are rather special classes of functions, and thus they require specialised regression techniques, which would enforce important theoretical properties, like commutativity or associativity. My presentation will address this issue in detail, and will discuss various regression methods applicable specifically to t-norms, uninorms and generalised means. I will also demonstrate software implementing these regression techniques, which would allow practitioners to paste their data and obtain optimal parameters of the chosen family of operators.<br /

Retrieving information from compressed XML documents according to vague queries

XML has become the standard way for representing and transforming data over the World Wide Web. The problem with XML documents is that they have a very high ratio of redundancy, which makes these documents demanding large storage capacity and high network band-width for transmission. Because of their extensive use, XML documents could be retrieved according to vague queries by naive users with poor background in writing XPath query. The aim of this thesis is to present the design of a system named “XML Compressing and Vague Querying (XCVQ)” which has the ability of compressing the XML document and retrieving the required information from the compressed version with less decompression required according to vague queries. XCVQ first compressed the XML document by separating its data into containers and then compress these containers using the GZip compressor. The compressed file could be retrieved if a vague query is submitted without the need to decompress the whole file. For the purpose of processing the vague queries, XCVQ decomposes the query according to the relevant documents and then a second decomposition stage is made according to the relevant containers. Only the required information is decompressed and submitted to the user. To the best of our knowledge, XCVQ is the first XML compressor that has the ability to process vague queries. The average compression ratio of the designed compressor is around 78% which may be considered competitive compared to other queriable XML compressors. Based on several experiments, the query processor part had the ability to answer different kinds of vague queries ranging from simple exact match queries to complex ones that require retrieving information from several compressed XML documents.EThOS - Electronic Theses Online ServiceGBUnited Kingdo