Entity Ranking on Graphs: Studies on Expert Finding

Todays web search engines try to offer services for finding various information in addition to simple web pages, like showing locations or answering simple fact queries. Understanding the association of named entities and documents is one of the key steps towards such semantic search tasks. This paper addresses the ranking of entities and models it in a graph-based relevance propagation framework. In particular we study the problem of expert finding as an example of an entity ranking task. Entity containment graphs are introduced that represent the relationship between text fragments on the one hand and their contained entities on the other hand. The paper shows how these graphs can be used to propagate relevance information from the pre-ranked text fragments to their entities. We use this propagation framework to model existing approaches to expert finding based on the entity's indegree and extend them by recursive relevance propagation based on a probabilistic random walk over the entity containment graphs. Experiments on the TREC expert search task compare the retrieval performance of the different graph and propagation models

Contribution structures

The invisibility of the individuals and groups that gave rise to requirements artifacts has been identified as a primary reason for the persistence of requirements traceability problems. This paper presents an approach, based on modelling the dynamic contribution structures underlying requirements artifacts, which addresses this issue. We show how these structures can be defined, using information about the agents who have contributed to artifact production, in conjunction with details of the numerous traceability relations that hold within and between artifacts themselves. We describe a scheme, derived from work in sociolinguistics, which can be used to indicate the capacities in which agents contribute. We then show how this information can be used to infer details about the social roles and commitments of agents with respect to their various contributions and to each other. We further propose a categorisation for artifact-based traceability relations and illustrate how they impinge on the identification and definition of these structures. Finally, we outline how this approach can be implemented and supported by tools, explain the means by which requirements change can be accommodated in the corresponding contribution structures, and demonstrate the potential it provides for "personnel-based" requirements traceability

Strategies to reduce nutrient pollution from manure management in China

As the demand for livestock products continues to increase in China, so too does the challenge of managing increasing quantities of manure. Urgent action is needed to control point source (housing, storage and processing) and diffuse (field application) pollution and improve the utilization of manure nutrients and organic matter. Here, we review strategies to improve management at each stage of the manure management chain and at different scales. Many strategies require infrastructure investment, e.g., for containment of all manure fractions. Engineering solutions are needed to develop advanced composting systems with lower environmental footprints and design more efficient nutrient stripping technologies. At the field-scale, there is an urgent need to develop a manure nutrient recommendation system that accounts for the range of manure types, cropping systems, soils and climates throughout China. At the regional scale, coordinated planning is necessary to promote recoupling of livestock and cropping systems, and reduce nutrient accumulation in regions with little available landbank, while minimizing the risk of pollution swapping from one region to another. A range of stakeholders are needed to support the step change and innovation required to improve manure management, reduce reliance on inorganic fertilizers, and generate new business opportunities

Representing and Reasoning on Conceptual Queries Over Image Databases

The problem of content management of multimedia data types (e.g., image, video, graphics) is becoming increasingly important with the development of advanced multimedia applications. Traditional database management systems are inadequate for the handling of such data types. They require new techniques for query formulation, retrieval, evaluation, and navigation. In this paper we develop a knowledge-based framework for modeling and retrieving image data by content. To represent the various aspects of an image object's characteristics, we propose a model which consists of three layers: (1) Feature and Content Layer, intended to contain image visual features such as contours, shapes,etc.; (2) Object Layer, which provides the (conceptual) content dimension of images; and (3) Schema Layer, which contains the structured abstractions of images, i.e., a general schema about the classes of objects represented in the object layer. We propose two abstract languages on the basis of description logics: one for describing knowledge of the object and schema layers, and the other, more expressive, for making queries. Queries can refer to the form dimension (i.e., information of the Feature and Content Layer) or to the content dimension (i.e., information of the Object Layer). These languages employ a variable free notation, and they are well suited for the design, verification and complexity analysis of algorithms. As the amount of information contained in the previous layers may be huge and operations performed at the Feature and Content Layer are time-consuming, resorting to the use of materialized views to process and optimize queries may be extremely useful. For that, we propose a formal framework for testing containment of a query in a view expressed in our query language. The algorithm we propose is sound and complete and relatively efficient.This is an extended version of the article in: Eleventh International Symposium on Methodologies for Intelligent Systems, Warsaw, Poland, 1999

Urban Containment Policies and Physical Activity A Time–Series Analysis of Metropolitan Areas, 1990–2002

Background: Urban containment policies attempt to manage the location, character, and timing of growth to support a variety of goals such as compact development, preservation of greenspace, and efficient use of infrastructure. Despite prior research evaluating the effects of urban containment policies on land use, housing, and transportation outcomes, the public health implications of these policies remain unexplored. This ecologic study examines relationships among urban containment policies, state adoption of growthmanagement legislation, and population levels of leisure and transportation-related physical activity in 63 large metropolitan statistical areas from 1990 to 2002. Methods: Multiple data sources were combined, including surveys of urban containment policies, the Behavioral Risk Factor Surveillance System, the U.S. Census of Population, the National Resources Inventory, and the Texas Transportation Institute Urban Mobility Study. Mixed models were used to examine whether urban containment policies and state adoption of growth-management legislation were associated with population levels of leisure-time physical activity (LTPA) and walking/bicycling to work over time. Results: Strong urban containment policies were associated with higher population levels of LTPA and walking/bicycling to work during the study period. Additionally, residents of states with legislation mandating urban growth boundaries reported significantly more minutes of LTPA/week compared to residents of states without such policies. Weak urban containment policies showed inconsistent relationships with physical activity. Conclusions: This study provides preliminary evidence that strong urban containment policies are associated with higher population levels of LTPA and active commuting. Future research should examine potential synergies among state, metropolitan, and local policy processes that may strengthen these relationship

Structured Knowledge Representation for Image Retrieval

We propose a structured approach to the problem of retrieval of images by content and present a description logic that has been devised for the semantic indexing and retrieval of images containing complex objects. As other approaches do, we start from low-level features extracted with image analysis to detect and characterize regions in an image. However, in contrast with feature-based approaches, we provide a syntax to describe segmented regions as basic objects and complex objects as compositions of basic ones. Then we introduce a companion extensional semantics for defining reasoning services, such as retrieval, classification, and subsumption. These services can be used for both exact and approximate matching, using similarity measures. Using our logical approach as a formal specification, we implemented a complete client-server image retrieval system, which allows a user to pose both queries by sketch and queries by example. A set of experiments has been carried out on a testbed of images to assess the retrieval capabilities of the system in comparison with expert users ranking. Results are presented adopting a well-established measure of quality borrowed from textual information retrieval

Reliability Analysis of Complex NASA Systems with Model-Based Engineering

The emergence of model-based engineering, with Model- Based Systems Engineering (MBSE) leading the way, is transforming design and analysis methodologies. The recognized benefits to systems development include moving from document-centric information systems and document-centric project communication to a model-centric environment in which control of design changes in the life cycles is facilitated. In addition, a single source of truth about the system, that is up-to-date in all respects of the design, becomes the authoritative source of data and information about the system. This promotes consistency and efficiency in regard to integration of the system elements as the design emerges and thereby may further optimize the design. Therefore Reliability Engineers (REs) supporting NASA missions must be integrated into model-based engineering to ensure the outputs of their analyses are relevant and value-needed to the design, development, and operational processes for failure risks assessment and communication