InfoFilter: Supporting Quality of Service for Fresh Information Delivery

With the explosive growth of the Internet and World Wide Web comes a dramatic increase in the number of users that compete for the shared resources of distributed system environments. Most implementations of application servers and distributed search software do not distinguish among requests to different web pages. This has the implication that the behavior of application servers is quite unpredictable. Applications that require timely delivery of fresh information consequently suffer the most in such competitive environments. This paper presents a model of quality of service (QoS) and the design of a QoS-enabled information delivery system that implements such a QoS modeL The goal of this development is two-fold. On one hand, we want to enable users or applications to specify the desired quality of service requ.irements for their requests so that application-aware QoS adaptation is supported throughout the Web query and search processing. On the other hand, we want to enable an application server to customize how it shou.ld respond to external requests by setting priorities among query requests and allocating server resources using adaptive QoS control mechanisms. We introduce the Infopipe approach as the systems support architecture and underlying technology for building a QoS-enabled distributed system for fresh information delivery

Digital Image Access & Retrieval

The 33th Annual Clinic on Library Applications of Data Processing, held at the University of Illinois at Urbana-Champaign in March of 1996, addressed the theme of "Digital Image Access & Retrieval." The papers from this conference cover a wide range of topics concerning digital imaging technology for visual resource collections. Papers covered three general areas: (1) systems, planning, and implementation; (2) automatic and semi-automatic indexing; and (3) preservation with the bulk of the conference focusing on indexing and retrieval.published or submitted for publicatio

The effect of dyslexia on information retrieval: A pilot study

Purpose – The purpose of the paper is to resolve a gap in our knowledge of how people with dyslexia interact with Information Retrieval (IR) systems, specifically an understanding of their information searching behaviour. Very little research has been undertaken with this particular user group, and given the size of the group (an estimated 10% of the population) this lack of knowledge needs to be addressed. Design/Methodology/Approach - We use elements of the dyslexia cognitive profile to design a logging system recording the difference between two sets of participants: dyslexic and control users. We use a standard Okapi interface together with two standard TREC topics in order to record the information searching behaviour of these users. We gather evidence from various sources, including quantitative information on search logs, together with qualitative information from interviews and questionnaires. We record variables on queries, documents, relevance assessments and sessions in the search logs. We use this evidence to examine the difference in searching between the two sets of users, in order to understand the effect of dyslexia on the information searching behaviour. A topic analysis is also conducted on the quantitative data to show any effect on the results from the information need. Research limitations/implications – As this is a pilot study, only 10 participants were recruited for the study, 5 for each user group. Due to ethical issues, the number of topics per search was restricted to one topic only. The study shows that the methodology applied is useful for distinguishing between the two user groups, taking into account differences between topic. We outline further research on the back of this pilot study in four main areas. A different approach from the proposed methodology is needed to measure the effect on query variables, which takes account of topic variation. More details on users are needed such as reading abilities, speed of language processing and working memory to distinguish the user groups. Effect of topic on search interaction must be measured in order to record the potential impact on the dyslexic user group. Work is needed on relevance assessment and effect on precision and recall for users who may not read many documents. Findings – Using the log data, we establish the differences in information searching behaviour of control and dyslexic users i.e. in the way the two groups interact with Okapi, and that qualitative information collected (such as experience etc) may not be able to account for these differences. Evidence from query variables was unable to distinguish between groups, but differences on topic for the same variables were recorded. Users who view more documents tended to judge more documents as being relevant, either in terms of the user group or topic. Session data indicated that there may be an important difference between the number of iterations used in a search between the user groups, as there may be little effect from the topic on this variable. Originality/Value – This is the first study of the effect of dyslexia on information search behaviour, and provides some evidence to take the field forward

Interactive context-aware user-driven metadata correction in digital libraries

Personal name variants are a common problem in digital libraries, reducing the precision of searches and complicating browsing-based interaction. The book-centric approach of name authority control has not scaled to match the growth and diversity of digital repositories. In this paper, we present a novel system for user-driven integration of name variants when interacting with web-based information-in particular digital library-systems. We approach these issues via a client-side JavaScript browser extension that can reorganize web content and also integrate remote data sources. Designed to be agnostic towards the web sites it is applied to, we illustrate the developed proof-of-concept system through worked examples using three different digital libraries. We discuss the extensibility of the approach in the context of other user-driven information systems and the growth of the Semantic Web

The National Transport Data Framework

Report by Professor Peter Landshoff (Cambridge University) and Professor John Polak (Imperial College London) on a project for the Department for Transport. emails: [email protected] [email protected] NTDF is designed to be a resource for data owners to deposit descriptions into a central catalogue, so that people can search for data and find data and understand their characteristics. The value of this is to individuals, to commercial organizations, and to public bodies. For example, services that provide better information to travellers will help to make their journey less stressful and persuade them to make more use of public transport. Transport operators need very diverse information to help them plan developments to their services: demographic, geographical, economic etc. And policy makers need a similar range of information to help them decide how to divide their budget and afterwards to evaluate how valuable it has been.This work was supported by the Department for Transport (DfT)

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Measuring and Managing Answer Quality for Online Data-Intensive Services

Online data-intensive services parallelize query execution across distributed software components. Interactive response time is a priority, so online query executions return answers without waiting for slow running components to finish. However, data from these slow components could lead to better answers. We propose Ubora, an approach to measure the effect of slow running components on the quality of answers. Ubora randomly samples online queries and executes them twice. The first execution elides data from slow components and provides fast online answers; the second execution waits for all components to complete. Ubora uses memoization to speed up mature executions by replaying network messages exchanged between components. Our systems-level implementation works for a wide range of platforms, including Hadoop/Yarn, Apache Lucene, the EasyRec Recommendation Engine, and the OpenEphyra question answering system. Ubora computes answer quality much faster than competing approaches that do not use memoization. With Ubora, we show that answer quality can and should be used to guide online admission control. Our adaptive controller processed 37% more queries than a competing controller guided by the rate of timeouts.Comment: Technical Repor