Developing transactive memory systems : theoretical contributions from a social identity perspective

Transactive memory system (TMS) theory explains how expertise is recognized and coordinated in teams. Extending current TMS research from a group information-processing perspective, our article presents a theoretical model that considers TMS development from a social identity perspective. We discuss how two features of communication (quantity and quality) important to TMS development are linked to TMS through the group identification mechanism of a shared common team identity. Informed by social identity theory, we also differentiate between intragroup and intergroup contexts and outline how, in multidisciplinary teams, professional identification and perceived equality of status among professional subgroups have a role to play in TMS development. We provide a theoretical discussion of future research directions aimed at testing and extending our model.

The ranking based constrained document clustering method and its application to social event detection

With the growing size and variety of social media files on the web, it’s becoming critical to efficiently organize them into clusters for further processing. This paper presents a novel scalable constrained document clustering method that harnesses the power of search engines capable of dealing with large text data. Instead of calculating distance between the documents and all of the clusters’ centroids, a neighborhood of best cluster candidates is chosen using a document ranking scheme. To make the method faster and less memory dependable, the in-memory and in-database processing are combined in a semi-incremental manner. This method has been extensively tested in the social event detection application. Empirical analysis shows that the proposed method is efficient both in computation and memory usage while producing notable accuracy.

Understanding negation and family history to improve clinical information retrieval

We present a study to understand the effect that negated terms (e.g., "no fever") and family history (e.g., "family history of diabetes") have on searching clinical records. Our analysis is aimed at devising the most effective means of handling negation and family history. In doing so, we explicitly represent a clinical record according to its different content types: negated, family history and normal content; the retrieval model weights each of these separately. Empirical evaluation shows that overall the presence of negation harms retrieval effectiveness while family history has little effect. We show negation is best handled by weighting negated content (rather than the common practise of removing or replacing it). However, we also show that many queries benefit from the inclusion of negated content and that negation is optimally handled on a per-query basis. Additional evaluation shows that adaptive handing of negated and family history content can have significant benefits.

Relevation! : an open source system for information retrieval relevance assessment

Relevation! is a system for performing relevance judgements for information retrieval evaluation. Relevation! is web-based, fully configurable and expandable; it allows researchers to effectively collect assessments and additional qualitative data. The system is easily deployed allowing assessors to smoothly perform their relevance judging tasks, even remotely. Relevation! is available as an open source project at: http://ielab.github.io/relevation.

Top-k retrieval using facility location analysis

The top-k retrieval problem aims to find the optimal set of k documents from a number of relevant documents given the user’s query. The key issue is to balance the relevance and diversity of the top-k search results. In this paper, we address this problem using Facility Location Analysis taken from Operations Research, where the locations of facilities are optimally chosen according to some criteria. We show how this analysis technique is a generalization of state-of-the-art retrieval models for diversification (such as the Modern Portfolio Theory for Information Retrieval), which treat the top-k search results like “obnoxious facilities” that should be dispersed as far as possible from each other. However, Facility Location Analysis suggests that the top-k search results could be treated like “desirable facilities” to be placed as close as possible to their customers. This leads to a new top-k retrieval model where the best representatives of the relevant documents are selected. In a series of experiments conducted on two TREC diversity collections, we show that significant improvements can be made over the current state-of-the-art through this alternative treatment of the top-k retrieval problem.

An analysis of ranking principles and retrieval strategies

The assumptions underlying the Probability Ranking Principle (PRP) have led to a number of alternative approaches that cater or compensate for the PRP’s limitations. All alternatives deviate from the PRP by incorporating dependencies. This results in a re-ranking that promotes or demotes documents depending upon their relationship with the documents that have been already ranked. In this paper, we compare and contrast the behaviour of state-of-the-art ranking strategies and principles. To do so, we tease out analytical relationships between the ranking approaches and we investigate the document kinematics to visualise the effects of the different approaches on document ranking.

When two is better than one : a study of ranking paradigms and their integrations for subtopic retrieval

In this paper, we consider the problem of document ranking in a non-traditional retrieval task, called subtopic retrieval. This task involves promoting relevant documents that cover many subtopics of a query at early ranks, providing thus diversity within the ranking. In the past years, several approaches have been proposed to diversify retrieval results. These approaches can be classified into two main paradigms, depending upon how the ranks of documents are revised for promoting diversity. In the first approach subtopic diversification is achieved implicitly, by choosing documents that are different from each other, while in the second approach this is done explicitly, by estimating the subtopics covered by documents. Within this context, we compare methods belonging to the two paradigms. Furthermore, we investigate possible strategies for integrating the two paradigms with the aim of formulating a new ranking method for subtopic retrieval. We conduct a number of experiments to empirically validate and contrast the state-of-the-art approaches as well as instantiations of our integration approach. The results show that the integration approach outperforms state-of-the-art strategies with respect to a number of measures.

University of Glasgow at ImageCLEFPhoto 2009 : optimising similarity and diversity in image retrieval

In this paper we describe the approaches adopted to generate the runs submitted to ImageCLEFPhoto 2009 with an aim to promote document diversity in the rankings. Four of our runs are text based approaches that employ textual statistics extracted from the captions of images, i.e. MMR [1] as a state of the art method for result diversification, two approaches that combine relevance information and clustering techniques, and an instantiation of Quantum Probability Ranking Principle. The fifth run exploits visual features of the provided images to re-rank the initial results by means of Factor Analysis. The results reveal that our methods based on only text captions consistently improve the performance of the respective baselines, while the approach that combines visual features with textual statistics shows lower levels of improvements.

The Quantum Probability Ranking Principle for Information Retrieval

While the Probability Ranking Principle for Information Retrieval provides the basis for formal models, it makes a very strong assumption regarding the dependence between documents. However, it has been observed that in real situations this assumption does not always hold. In this paper we propose a reformulation of the Probability Ranking Principle based on quantum theory. Quantum probability theory naturally includes interference effects between events. We posit that this interference captures the dependency between the judgement of document relevance. The outcome is a more sophisticated principle, the Quantum Probability Ranking Principle, that provides a more sensitive ranking which caters for interference/dependence between documents’ relevance.

Peripheral vision benefits spatial learning by guiding eye movements

The loss of peripheral vision impairs spatial learning and navigation. However, the mechanisms underlying these impairments remain poorly understood. One advantage of having peripheral vision is that objects in an environment are easily detected and readily foveated via eye movements. The present study examined this potential benefit of peripheral vision by investigating whether competent performance in spatial learning requires effective eye movements. In Experiment 1, participants learned room-sized spatial layouts with or without restriction on direct eye movements to objects. Eye movements were restricted by having participants view the objects through small apertures in front of their eyes. Results showed that impeding effective eye movements made subsequent retrieval of spatial memory slower and less accurate. The small apertures also occluded much of the environmental surroundings, but the importance of this kind of occlusion was ruled out in Experiment 2 by showing that participants exhibited intact learning of the same spatial layouts when luminescent objects were viewed in an otherwise dark room. Together, these findings suggest that one of the roles of peripheral vision in spatial learning is to guide eye movements, highlighting the importance of spatial information derived from eye movements for learning environmental layouts.

Orientation dependence of spatial memory acquired from auditory experience

The present study investigated whether memory for a room-sized spatial layout learned through auditory localization of sounds exhibits orientation dependence similar to that observed for spatial memory acquired from stationary viewing of the environment. Participants learned spatial layouts by viewing objects or localizing sounds and then performed judgments of relative direction among remembered locations. The results showed that direction judgments following auditory learning were performed most accurately at a particular orientation in the same way as were those following visual learning, indicating that auditorily encoded spatial memory is orientation dependent. In combination with previous findings that spatial memories derived from haptic and proprioceptive experiences are also orientation dependent, the present finding suggests that orientation dependence is a general functional property of human spatial memory independent of learning modality.

Visual and proprioceptive representations in spatial memory

It has been shown that spatial information can be acquired from both visual and nonvisual modalities. The present study explored how spatial information from vision and proprioception was represented in memory, investigating orientation dependence of spatial memories acquired through visual and proprioceptive spatial learning. Experiment 1 examined whether visual learning alone and proprioceptive learning alone yielded orientation-dependent spatial memory. Results showed that spatial memories from both types of learning were orientation dependent. Experiment 2 explored how different orientations of the same environment were represented when they were learned visually and proprioceptively. Results showed that both visually and proprioceptively learned orientations were represented in spatial memory, suggesting that participants established two different reference systems based on each type of learning experience and interpreted the environment in terms of these two reference systems. The results provide some initial clues to how different modalities make unique contributions to spatial representations.

Common secure index for conjunctive keyword-based retrieval over encrypted data

We consider the following problem: users in a dynamic group store their encrypted documents on an untrusted server, and wish to retrieve documents containing some keywords without any loss of data confidentiality. In this paper, we investigate common secure indices which can make multi-users in a dynamic group to obtain securely the encrypted documents shared among the group members without re-encrypting them. We give a formal definition of common secure index for conjunctive keyword-based retrieval over encrypted data (CSI-CKR), define the security requirement for CSI-CKR, and construct a CSI-CKR based on dynamic accumulators, Paillier’s cryptosystem and blind signatures. The security of proposed scheme is proved under strong RSA and co-DDH assumptions.