Information retrieval (IR) systems exploit relevant information when tailoring search results to individual information needs. However, current search experience becomes poor without considering similar queries entered by previous searchers. In the following paper, we discuss a solution to this problem, which combines collaborative filtering algorithms with traditional IR models to enable EIR. We also present various iterative refinement methods for improving the raw performance of this system. We validate our theories in an experiment using queries extracted from the click-through log of a commercial search engine. According to our results, an IR system employing iteratively refined, collaborative retrieval significantly outperforms various baseline retrieval models.

Research suggests that browsing clinical guidelines in a linear format is difficult for users. One national producer of clinical guidelines (HAS, the French National Authority for Health) has recently developed a new document format designed to improve accessibility. It is a limited-depth hypertext structurally constrained so that all information lies within two clicks of a central index ('reco2clics'). In the following paper, we introduce an authoring tool which converts full-length clinical guidelines to the 'reco2clics' format. Alongside routine editorial operations, this tool supports dynamic document restructuring, a complex operation using text segmentation algorithms and deontic analysis.

Professional users of medical information often report difficulties when attempting to locate specific information in lengthy documents. Sometimes these difficulties can be attributed to poorly specified section titles which fail to advertise relevant content. In this paper we describe preliminary work on a software plug-in for a document engineering environment that will assist authors when they formulate section-level headings. We describe two different algorithms which can be used to generate section titles. We compare the performance of these algorithms and correlate our experimental results with an evaluation of title quality performed by domain experts.

Previous work has established that search engine queries can be classified according to the intent of the searcher (i.e., why is the user searching, what specifically do they intend to do). In this article, we describe an experiment in which four sets of queries, each set representing a different user intent, are repeatedly submitted to three search engines over a period of 60 days. Using a variety of measurements, we describe the overall stability of the search engine results recorded for each group. Our findings suggest that search engine results for informational queries are significantly more stable than the results obtained using transactional, navigational, or commercial queries.

Previous work has established that specific linguistic markers present in specialised medical documents (clinical guidelines) can be used to support their automatic structuring within a document engineering environment. This technique is commonly used by the French Health Authority (la Haute Autorite de Sante) during elaboration of clinical guidelines to improve the quality of the final document. In this paper, we explore the readability of clinical guidelines. We discuss a structural measure of document readability that exploits the ratio between these linguistic markers (deontic structures) and the remainder of the text. We describe an experiment in which a corpus of 10 French clinical guidelines is scored for structural readability. We correlate these scores with measures of textual cohesion (computed using latent semantic analysis) and the results of a readability survey performed by a panel of domain experts. Our results suggest an association between the density of deontic structures in a clinical guideline and its overall readability. This implies that certain generic readability measures can henceforth be utilised in our document engineering environment.

In this paper we look at how images can be labelled as a result of click throughs from searches. One approach acts as a filter on image searches specifically, while the other approach propagates labels to images from their containing pages, where those pages were labelled themselves using clickthrough as a filter on text search. Then the paper reports on an experiment where users ranked for relevance six methods for labelling images, comparing the two clickthrough-based methods with flickr's amateur explicit labelling, Getty's professional explicit labelling, Google's standard image search, and the new Google Image Labeller. As well as comparing the accuracy of the proposed image labelling methods and discovering that automatic methods outperform explicit human labelling methods, the experiment suggests clickthrough data is reliable with very few clicks for image classification purposes.

In this article we describe a hybrid technique for dictionary-based query translation suitable for English-Chinese cross language information retrieval. This technique marries a graph-based model for the resolution of candidate term ambiguity with a pattern-based method for the translation of out-of-vocabulary (OOV) terms. We evaluate the performance of this hybrid technique in an experiment using several NTCIR test collections. Experimental results indicate a substantial increase in retrieval effectiveness over various baseline systems incorporating machine- and dictionary-based translation.

Lexical ambiguity in query-based image retrieval is an immemorial problem which has seemingly resisted all countermeasures. In this paper we introduce a methodology that expresses the users of a system and their navigational behaviour as the paramount resource for resolving query term ambiguity. Mass user consensus is modelled within a multi-dimensional feature space and evaluated through cluster analysis. This technique resolves query term ambiguity in a wholly democratic and dynamic fashion, in contrast to the brittle centralised models of contemporary word sense classification systems. The simple approach contained herein leads to several interesting emergent properties.