Complementarity and Similarity: Relationships Between Text-Mined Terms and Social Tags for Image Description

In this paper, we present our results on comparing the language of social tags with text-mined terms for images. We have developed a novel modification of the standard term frequency/inverse document frequency metric (tf*idf) (Salton & Buckley 1988) over tags and terms to identify and filter terms which discriminate images for searchers. Since tags serve as additional input, we refer to this modification as the T-tf*idf Measure, i.e. Tags-term frequency as an inverse of document frequency, where "document" in this case refers to the either the tag or term dataset. We present the results of several variations on this measure, and demonstrate the impact on output. We discuss evaluation of our results on the ability of the metric to reflect human judgments through experiments which illustrate the value of the approach

A Framework for Multi-Valued Reasoning over Inconsistent Viewpoints

In requirements elicitation, different stakeholders often hold different views of how a proposed system should behave, resulting in inconsistencies between their descriptions. Consensus may not be needed for every detail, but it can be hard to determine whether a particular disagreement affects the critical properties of the system. In this paper, we describe the # bel framework for merging and reasoning about multiple, inconsistent state machine models. # bel permits the analyst to choose how to combine information from the multiple viewpoints, where each viewpoint is described using an underlying multi-valued logic. The different values of our logics typically represent different levels of agreement. Our multi-valued model checker, # chek, allows us to check the merged model against properties expressed in a temporal logic. The resulting framework can be used as an exploration tool to support requirements negotiation, by determining what properties are preserved for various combinations of inconsistent viewpoints

Managing the consistency of distributed documents

Many businesses produce documents as part of their daily activities: software engineers produce requirements specifications, design models, source code, build scripts and more; business analysts produce glossaries, use cases, organisation charts, and domain ontology models; service providers and retailers produce catalogues, customer data, purchase orders, invoices and web pages. What these examples have in common is that the content of documents is often semantically related: source code should be consistent with the design model, a domain ontology may refer to employees in an organisation chart, and invoices to customers should be consistent with stored customer data and purchase orders. As businesses grow and documents are added, it becomes difficult to manually track and check the increasingly complex relationships between documents. The problem is compounded by current trends towards distributed working, either over the Internet or over a global corporate network in large organisations. This adds complexity as related information is not only scattered over a number of documents, but the documents themselves are distributed across multiple physical locations. This thesis addresses the problem of managing the consistency of distributed and possibly heterogeneous documents. “Documents” is used here as an abstract term, and does not necessarily refer to a human readable textual representation. We use the word to stand for a file or data source holding structured information, like a database table, or some source of semi-structured information, like a file of comma-separated values or a document represented in a hypertext markup language like XML [Bray et al., 2000]. Document heterogeneity comes into play when data with similar semantics is represented in different ways: for example, a design model may store a class as a rectangle in a diagram whereas a source code file will embed it as a textual string; and an invoice may contain an invoice identifier that is composed of a customer name and date, both of which may be recorded and managed separately. Consistency management in this setting encompasses a number of steps. Firstly, checks must be executed in order to determine the consistency status of documents. Documents are inconsistent if their internal elements hold values that do not meet the properties expected in the application domain or if there are conflicts between the values of elements in multiple documents. The results of a consistency check have to be accumulated and reported back to the user. And finally, the user may choose to change the documents to bring them into a consistent state. The current generation of tools and techniques is not always sufficiently equipped to deal with this problem. Consistency checking is mostly tightly integrated or hardcoded into tools, leading to problems with extensibility with respect to new types of documents. Many tools do not support checks of distributed data, insisting instead on accumulating everything in a centralized repository. This may not always be possible, due to organisational or time constraints, and can represent excessive overhead if the only purpose of integration is to improve data consistency rather than deriving any additional benefit. This thesis investigates the theoretical background and practical support necessary to support consistency management of distributed documents. It makes a number of contributions to the state of the art, and the overall approach is validated in significant case studies that provide evidence of its practicality and usefulness