The use of implicit evidence for relevance feedback in web retrieval

In this paper we report on the application of two contrasting types of relevance feedback for web retrieval. We compare two systems; one using explicit relevance feedback (where searchers explicitly have to mark documents relevant) and one using implicit relevance feedback (where the system endeavours to estimate relevance by mining the searcher's interaction). The feedback is used to update the display according to the user's interaction. Our research focuses on the degree to which implicit evidence of document relevance can be substituted for explicit evidence. We examine the two variations in terms of both user opinion and search effectiveness

Supporting searching on small screen devices using summarisation

In recent years, small screen devices have seen widespread increase in their acceptance and use. Combining mobility with their increased technological advances many such devices can now be considered mobile information terminals. However, user interactions with small screen devices remain a challenge due to the inherent limited display capabilities. These challenges are particularly evident for tasks, such as information seeking. In this paper we assess the effectiveness of using hierarchical-query biased summaries as a means of supporting the results of an information search conducted on a small screen device, a PDA. We present the results of an experiment focused on measuring users' perception of relevance of displayed documents, in the form of automatically generated summaries of increasing length, in response to a simulated submitted query. The aim is to study experimentally how users' perception of relevance varies depending on the length of summary, in relation to the characteristics of the PDA interface on which the content is presented. Experimental results suggest that hierarchical query-biased summaries are useful and assist users in making relevance judgments

A study of factors affecting the utility of implicit relevance feedback

Implicit relevance feedback (IRF) is the process by which a search system unobtrusively gathers evidence on searcher interests from their interaction with the system. IRF is a new method of gathering information on user interest and, if IRF is to be used in operational IR systems, it is important to establish when it performs well and when it performs poorly. In this paper we investigate how the use and effectiveness of IRF is affected by three factors: search task complexity, the search experience of the user and the stage in the search. Our findings suggest that all three of these factors contribute to the utility of IRF

A study of interface support mechanisms for interactive information retrieval

Advances in search technology have meant that search systems can now offer assistance to users beyond simply retrieving a set of documents. For example, search systems are now capable of inferring user interests by observing their interaction, offering suggestions about what terms could be used in a query, or reorganizing search results to make exploration of retrieved material more effective. When providing new search functionality, system designers must decide how the new functionality should be offered to users. One major choice is between (a) offering automatic features that require little human input, but give little human control; or (b) interactive features which allow human control over how the feature is used, but often give little guidance over how the feature should be best used. This article presents a study in which we empirically investigate the issue of control by presenting an experiment in which participants were asked to interact with three experimental systems that vary the degree of control they had in creating queries, indicating which results are relevant in making search decisions. We use our findings to discuss why and how the control users want over search decisions can vary depending on the nature of the decisions and the impact of those decisions on the user's search

Overview of the personalized and collaborative information retrieval (PIR) track at FIRE-2011

The Personalized and collaborative Information Retrieval (PIR) track at FIRE 2011 was organized with an aim to extend standard information retrieval (IR) ad-hoc test collection design to facilitate research on personalized and collaborative IR by collecting additional meta-information during the topic (query) development process. A controlled query generation process through task-based activities with activity logging was used for each topic developer to construct the final list of topics. The standard ad-hoc collection is thus accompanied by a new set of thematically related topics and the associated log information. We believe this can better simulate a real-world search scenario and encourage mining user information from the logs to improve IR effectiveness. A set of 25 TREC formatted topics and the associated metadata of activity logs were released for the participants to use. In this paper we illustrate the data construction phase in detail and also outline two simple ways of using the additional information from the logs to improve retrieval effectiveness

Finding relevant documents using top ranking sentences: an evaluation of two alternative schemes

In this paper we present an evaluation of techniques that are designed to encourage web searchers to interact more with the results of a web search. Two specific techniques are examined: the presentation of sentences that highly match the searcher's query and the use of implicit evidence. Implicit evidence is evidence captured from the searcher's interaction with the retrieval results and is used to automatically update the display. Our evaluation concentrates on the effectiveness and subject perception of these techniques. The results show, with statistical significance, that the techniques are effective and efficient for information seeking

A survey on the use of relevance feedback for information access systems

Users of online search engines often find it difficult to express their need for information in the form of a query. However, if the user can identify examples of the kind of documents they require then they can employ a technique known as relevance feedback. Relevance feedback covers a range of techniques intended to improve a user's query and facilitate retrieval of information relevant to a user's information need. In this paper we survey relevance feedback techniques. We study both automatic techniques, in which the system modifies the user's query, and interactive techniques, in which the user has control over query modification. We also consider specific interfaces to relevance feedback systems and characteristics of searchers that can affect the use and success of relevance feedback systems

Query-biased web page summarisation: a task-oriented evaluation

We present a system that offers a new way of assessing web document relevance and new approach to the web-based evaluation of such a system. Provisionally named WebDocSum, the system is a query-biased web page summariser that aims to provide an alternative to the short, irrelevant abstracts typical of many web search result lists. Based on an initial evaluation the system appears to be more useful in helping users gauge document relevance than the traditional ranked titles/abstracts approach