13511072
Rutgers' HARD Track Experiences at TREC 2004
The goal of our work in the HARD track was to test techniques for using knowledge about various aspects of the information seeker’s context to improve IR system performance. We were particularly concerned with such knowledge which could be gained through implicit sources of evidence, rather than explicit questioning of the information seeker. We therefore did not submit any clarification form 1 , preferring to rely on the categories of supplied metadata concerning the user which we believed could, at least in principle, be inferred from user behavior, either in the past or during the current information seeking episode. The experimental condition of the HARD track was for each site to submit at least one baseline run for the set of 50 topics, using only the title and (optionally) description fields for query construction. The results of the baseline run(s) were compared with the results from one or more experimental runs, which made use of the supplied searcher metadata, and of a clarification form submitted to the searcher, asking for whatever information each site thought would be useful in improving search results. We used only the supplied metadata, for the reasons stated above, and especially because we were interested in how to make initial queries better, rather than in how to conduct a dialogue with a searcher. There were five categories of searcher metadata for each topic (not all topics had values for all five): Genre, Familiarity, Geography, Granularity and Related text(s), which were intended to represent aspects of the searcher’s context which might be useful in tailoring retrieval to the individual, and the individual situation. We made the assumption that at least some of these categories would be available to the IR system prior to (or in conjunction with) the specific search session, either through explicit or implicit evidence. Therefore, for us the HARD track experimental condition was designed to test whether knowledge of these contextual characteristics, and our specific ways of using that knowledge, would result in better retrieval performance than a good IR system without such knowledge. We understood that there would be, in general, two ways in which to take account of the metadata. One would be to modify the initial query from the (presumed) searcher, before submitting it for search; the other would be to search with the initial query, and then to modify (i.e. re-rank) the results before showing them to the searcher. We used both, but mainly concentrated on the latter of these techniques in taking account of the different types of metadata. 2 Hypotheses for How to Take Account of Metadata Categories and Values Our general approach was to generate hypotheses about how to take account of each of the categories of metadata information in order to improve retrieval effectiveness, to operationalize them in the TREC HARD setting, to test each hypothesis individually on the training corpus, and then to combine the best-performing ones from each category to generate a final result list for the test corpus. Below are summarized the various improvement methods used based on metadata: Table 1. Methods for improving retrieval effectiveness based on metadata.
205485574
Assessing term effectiveness in the interactive information access process
This study addresses the question of whether the way in which sets of query terms are identified has an impact on the effectiveness of users' information seeking efforts. Query terms are text strings used as input to an information access system; they are products of a method or grammar that identifies a set of query terms. We conducted an experiment that compared the effectiveness of sets of query terms identified for a single book by three different methods. One had been previously prepared by a human indexer for a back-of-the-book index. The other two were identified by computer programs that used a combination of linguistic and statistical criteria to extract terms from full text. Effectiveness was measured by (1) whether selected query terms led participants to correct answers and (2) how long it took participants to obtain correct answers. Our results show that two sets of terms - the human terms and the set selected according to the linguistically more sophisticated criteria - were significantly more effective than the third set of terms. This single case demonstrates that query languages do have a measurable impact on the effectiveness of query term languages in the interactive information access process. The procedure described in this paper can be used to assess the effectiveness for information seekers of query terms identified by any query language.
22924389
User preference: A measure of query-term quality
16330464
Detecting Document Genre for Personalization of Information Retrieval
We report on the effectiveness of language models for personalization of retrieval results based on a searcher’s preference for document genre. In principle, such preferences can be obtained via implicit relevance feedback through the observation of the searcher’s actions and behavior during search sessions. While our approach did not produce significant improvement to retrieval effectiveness, the methodology and experimental setting can and are being used for further work on exploring genre-based personalization.
3132637
Selecting books: a performance-based study
Our research compares the impact of paper vs. electronic presentation of text on the book selection process. Our focus is on the stage of book selection in which users study the content of a book to decide whether it is useful for their intended purpose. Effectiveness is operationalized as accurate determination of whether a non-fiction book contains enough discussion of a particular topic to be useful for a research paper. 24 undergraduates participated in a balanced study in which they were given a topic-book pair and asked to decide whether the book was useful for the topic. We explore the differences in performance, with specific reference to the role of the search function, table-of-contents and index
14971936
Does Familiarity Breed Content? Taking Account of Familiarity with a Topic in Personalizing Information Retrieval
We report on an evaluation of the effectiveness of considering a user's familiarity with a topic in improving information retrieval performance. This approach to personalization is based on previous results indicating differences in user search behavior and judgments according to his/her familiarity to the topic explored, and to research on using implicit sources of evidence to determine the user's context and preferences. Our attempt was to relate a topic-dependent concept and measure, familiarity with the topic, with topic-independent measures of documents such as readability, concreteness/abstractness, and specificity/generality. Contrary to our expectations, a user’s familiarity with a topic has no effect on the utility of readability or concrete/abstract scoring. We are encouraged, however, to find that high readability had a positive effect on search results, regardless of a user’s familiarity with a topic.
8904843
Social Peer-to-Peer for Resource Discovery
For resource discovery in social networks, people can directly contact some acquaintances that have knowledge about the resources they are looking for. However, in current peer-to-peer networks, peer nodes lack capabilities similar to social networks, making it difficult to route queries efficiently. In this paper, we present a social-like system (Social-P2P) for resource discovery by mimicking human behaviours in social networks. Different from most informed search algorithms, peer nodes learn knowledge from the results of previous searches and no additional overhead is required to obtain extra information from neighbouring nodes. Unlike community-based P2P information sharing systems, we do not intend to create and maintain peer groups or communities consciously. Peer nodes with the same interests will be highly connected to each other spontaneously. Social-P2P has been simulated in a dynamic environment. From the simulation results and analysis, Social-P2P achieved better performance than current methods
2746167
Modelling and simulation of Network Enabled Capability on service-oriented architecture
Network Enabled Capability (NEC) is the UK Ministry of Defence’s response to the quickly changing conflict environment in which its forces must operate. In NEC, systems need to be integrated in context, to assist in human activity and provide dependable inter-operation. In this paper, we present our research work in the NECTISE project with a focus on the modelling and simulation of service-oriented architecture (SOA) for delivering dependable and sustainable military capability. The simulation results indicate that the proposed architectural model can provide a high-level of reliability and sustainability in the provision of capability in a dynamic environment. Moreover, a NEC demonstration system for regional surveillance is introduced in this paper to illustrate the use of SOA to achieve NEC.
6788128
Airport Internal Safety Risk Assessment using Fuzzy Hierarchy Process Approach
This paper offers an assessment of airport internal safety risk. It deals with general concept of risk and safety, describes the main causes of airport risk. A model based on fuzzy simulation technique and hierarchical structure analysis is developed to evaluate the airport internal safety risk. With the use of linguistic terms, subjective assessments of qualitative safety risk indexes are represented with fuzzy variable. The relative weights of safety attributes are assessed using a pairwise comparison process. Based on the concept of optimality, fuzzy simulation approach is employed to dispose of the evaluation model and compute the expected values. Then the shortcoming of the traditional analytic hierarchy process (AHP) is made up. Finally, an empirical study about a major domestic airport is conducted to demonstrate the effectiveness of the approach.
14622249
Knowledge Inventory Management Using Actuarial Method
Knowledge inventory management is nowadays central issue as knowledge management becomes vital for organizations. Knowledge inventory management involves acquiring, retaining, deploying, idling, and abandoning technologies. Managers must make investment decisions about which technologies should be involved into inventory for future usage. Options-pricing model (OPM) has been widely accepted to make investment decisions. An alternative technology is regarded as an option to switch technologies to deal with future contingencies. This paper studies another kind of knowledge inventory problem which OPM is sort of inefficient to deal with. An organization might be forced to invest in some technology in the future because of some specific incident occurs, thus option is replaced by obligation. The characteristics of this kind of problem are portrayed and we show why OPM is not applicable. We treat the specific incident as an insurance accident to organizations and initial investment in some technology as insurance fee which can cover the loss when accident occurs. We use actuarial model to analyze the problem and give the evaluation methods in different conditions.
15166655
The Vector Data Management of GIS Based on PDA
Traditionally, vector data of GIS based on PDA is managed with a traditional pyramid model to promote displaying speed. However, this pyramid model does not flexible or practical enough to solve many problems, neither the data file designing and data processing method are discussed before. Therefore, in this paper, an improved pyramid model is proposed and a new data format for the model is designed, also, the data processing method is discussed. The experimental results show that, this solution is practical and efficient.