Local search: A guide for the information retrieval practitioner

There are a number of combinatorial optimisation problems in information retrieval in which the use of local search methods are worthwhile. The purpose of this paper is to show how local search can be used to solve some well known tasks in information retrieval (IR), how previous research in the field is piecemeal, bereft of a structure and methodologically flawed, and to suggest more rigorous ways of applying local search methods to solve IR problems. We provide a query based taxonomy for analysing the use of local search in IR tasks and an overview of issues such as fitness functions, statistical significance and test collections when conducting experiments on combinatorial optimisation problems. The paper gives a guide on the pitfalls and problems for IR practitioners who wish to use local search to solve their research issues, and gives practical advice on the use of such methods. The query based taxonomy is a novel structure which can be used by the IR practitioner in order to examine the use of local search in IR

DESIGN OF EFFICIENT IN-NETWORK DATA PROCESSING AND DISSEMINATION FOR VANETS

By providing vehicle-to-vehicle and vehicle-to-infrastructure wireless communications, vehicular ad hoc networks (VANETs), also known as the “networks on wheels”, can greatly enhance traffic safety, traffic efficiency and driving experience for intelligent transportation system (ITS). However, the unique features of VANETs, such as high mobility and uneven distribution of vehicular nodes, impose critical challenges of high efficiency and reliability for the implementation of VANETs. This dissertation is motivated by the great application potentials of VANETs in the design of efficient in-network data processing and dissemination. Considering the significance of message aggregation, data dissemination and data collection, this dissertation research targets at enhancing the traffic safety and traffic efficiency, as well as developing novel commercial applications, based on VANETs, following four aspects: 1) accurate and efficient message aggregation to detect on-road safety relevant events, 2) reliable data dissemination to reliably notify remote vehicles, 3) efficient and reliable spatial data collection from vehicular sensors, and 4) novel promising applications to exploit the commercial potentials of VANETs. Specifically, to enable cooperative detection of safety relevant events on the roads, the structure-less message aggregation (SLMA) scheme is proposed to improve communication efficiency and message accuracy. The scheme of relative position based message dissemination (RPB-MD) is proposed to reliably and efficiently disseminate messages to all intended vehicles in the zone-of-relevance in varying traffic density. Due to numerous vehicular sensor data available based on VANETs, the scheme of compressive sampling based data collection (CS-DC) is proposed to efficiently collect the spatial relevance data in a large scale, especially in the dense traffic. In addition, with novel and efficient solutions proposed for the application specific issues of data dissemination and data collection, several appealing value-added applications for VANETs are developed to exploit the commercial potentials of VANETs, namely general purpose automatic survey (GPAS), VANET-based ambient ad dissemination (VAAD) and VANET based vehicle performance monitoring and analysis (VehicleView). Thus, by improving the efficiency and reliability in in-network data processing and dissemination, including message aggregation, data dissemination and data collection, together with the development of novel promising applications, this dissertation will help push VANETs further to the stage of massive deployment

POLIS: a probabilistic summarisation logic for structured documents

PhDAs the availability of structured documents, formatted in markup languages such as SGML, RDF, or XML, increases, retrieval systems increasingly focus on the retrieval of document-elements, rather than entire documents. Additionally, abstraction layers in the form of formalised retrieval logics have allowed developers to include search facilities into numerous applications, without the need of having detailed knowledge of retrieval models. Although automatic document summarisation has been recognised as a useful tool for reducing the workload of information system users, very few such abstraction layers have been developed for the task of automatic document summarisation. This thesis describes the development of an abstraction logic for summarisation, called POLIS, which provides users (such as developers or knowledge engineers) with a high-level access to summarisation facilities. Furthermore, POLIS allows users to exploit the hierarchical information provided by structured documents. The development of POLIS is carried out in a step-by-step way. We start by defining a series of probabilistic summarisation models, which provide weights to document-elements at a user selected level. These summarisation models are those accessible through POLIS. The formal definition of POLIS is performed in three steps. We start by providing a syntax for POLIS, through which users/knowledge engineers interact with the logic. This is followed by a definition of the logics semantics. Finally, we provide details of an implementation of POLIS. The final chapters of this dissertation are concerned with the evaluation of POLIS, which is conducted in two stages. Firstly, we evaluate the performance of the summarisation models by applying POLIS to two test collections, the DUC AQUAINT corpus, and the INEX IEEE corpus. This is followed by application scenarios for POLIS, in which we discuss how POLIS can be used in specific IR tasks

A Query-Centric Approach to Supporting the Development of Context-Aware Applications for Mobile Ad Hoc Networks, Doctoral Dissertation, August 2006

The wide-spread use of mobile computing devices has led to an increased demand for applications that operate dependably in opportunistically formed networks. A promising approach to supporting software development for such dynamic settings is to rely on the context-aware computing paradigm, in which an application views the state of the surrounding ad hoc network as a valuable source of contextual information that can be used to adapt its behavior. Collecting context information distributed across a constantly changing network remains a significant technical challenge. This dissertation presents a query-centered approach to simplifying context interactions in mobile ad hoc networks. Using such an approach, an application programmer views the surrounding world asa single data repository over which descriptive queries can be issued. Distributed context information appears to be locally available, effectively hiding the complex networking tasks required to acquire context in an open and dynamic setting. This dissertation identifies the research issues associated with developing a query-centric approach and discusses solutions to providing query-centric support to application developers. To promote rapid and dependable software development, a query-centric middleware is provided to the application programmer. These solutions provide the means to reason about the correctness of an application\u27s design and potentially to reduce programmer effort and error

Enhancing Query Reformulation Performance by Combining Content and Hypertext Analyses

Information retrieval techniques play a critical role in the development of the information systems. Different searches have focused on the way of improving the retrieval effectiveness. Query expansion via relevance feedback is a good technique that proved to be a good way to improve the retrieval performance. In this paper, we investigate new methods to improve the query reformulation process. A two step process is employed to reformulate query. In a preliminary step, a local set of documents is built from the retrieved result. In a second step, a co-occurrence analysis is performed on the local document set to deduce the terms to be used for the query expansion. To build the local set we use firstly a content-based analysis. It is a similarity study between the retrieved documents and the query. The second method combines content and hypertext analyses to achieve the local set construction. The TREC1 frame is used to evaluate the proposed processes

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