Updating collection representations for federated search

To facilitate the search for relevant information across a set of online distributed collections, a federated information retrieval system typically represents each collection, centrally, by a set of vocabularies or sampled documents. Accurate retrieval is therefore related to how precise each representation reflects the underlying content stored in that collection. As collections evolve over time, collection representations should also be updated to reflect any change, however, a current solution has not yet been proposed. In this study we examine both the implications of out-of-date representation sets on retrieval accuracy, as well as proposing three different policies for managing necessary updates. Each policy is evaluated on a testbed of forty-four dynamic collections over an eight-week period. Our findings show that out-of-date representations significantly degrade performance overtime, however, adopting a suitable update policy can minimise this problem

Design Patterns for Fusion-Based Object Retrieval

We address the task of ranking objects (such as people, blogs, or verticals) that, unlike documents, do not have direct term-based representations. To be able to match them against keyword queries, evidence needs to be amassed from documents that are associated with the given object. We present two design patterns, i.e., general reusable retrieval strategies, which are able to encompass most existing approaches from the past. One strategy combines evidence on the term level (early fusion), while the other does it on the document level (late fusion). We demonstrate the generality of these patterns by applying them to three different object retrieval tasks: expert finding, blog distillation, and vertical ranking.Comment: Proceedings of the 39th European conference on Advances in Information Retrieval (ECIR '17), 201

Anticipating Information Needs Based on Check-in Activity

In this work we address the development of a smart personal assistant that is capable of anticipating a user's information needs based on a novel type of context: the person's activity inferred from her check-in records on a location-based social network. Our main contribution is a method that translates a check-in activity into an information need, which is in turn addressed with an appropriate information card. This task is challenging because of the large number of possible activities and related information needs, which need to be addressed in a mobile dashboard that is limited in size. Our approach considers each possible activity that might follow after the last (and already finished) activity, and selects the top information cards such that they maximize the likelihood of satisfying the user's information needs for all possible future scenarios. The proposed models also incorporate knowledge about the temporal dynamics of information needs. Using a combination of historical check-in data and manual assessments collected via crowdsourcing, we show experimentally the effectiveness of our approach.Comment: Proceedings of the 10th ACM International Conference on Web Search and Data Mining (WSDM '17), 201

A genre analysis of reprint request emails written by EFL and physics professionals

The present study aimed to analyze reprint request e-mail messages written by postgraduates (MA students) of two fields of study, namely Physics and EFL, to realize the differences and similarities between the two email types. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The results showed that the two corpora were much alike at the level of move schemata while there were some differences concerning strategies and microstructural features. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing. The email writers within each discipline were affected by their previously learned texts and the physics group was affected by the conventions of Persian letter writing<br /

Adaptive query-based sampling of distributed collections

As part of a Distributed Information Retrieval system a de-scription of each remote information resource, archive or repository is usually stored centrally in order to facilitate resource selection. The ac-quisition ofprecise resourcedescriptionsistherefore animportantphase in Distributed Information Retrieval, as the quality of such represen-tations will impact on selection accuracy, and ultimately retrieval per-formance. While Query-Based Sampling is currently used for content discovery of uncooperative resources, the application of this technique is dependent upon heuristic guidelines to determine when a sufficiently accurate representation of each remote resource has been obtained. In this paper we address this shortcoming by using the Predictive Likelihood to provide both an indication of thequality of an acquired resource description estimate, and when a sufficiently good representation of a resource hasbeen obtained during Query-Based Sampling

A complex dural-venous variation in the posterior cranial fossa: a triplicate falx cerebelli and an aberrant venous sinus

Variations of the dural folds and the dural venous sinuses are seldom reported in the extant medical literature. Such variations in the posterior cranial fossa may be problematic in various diagnostic and operative procedures of this region. We report our observation of an extremely rare variation of the falx cerebelli and posterior cranial fossa venous sinuses encountered upon dissection of a young male cadaver. In this specimen the falx cerebelli was duplicated with dimensions of 45.3 × 5.1 mm and 49.8 × 5.3 mm for the right and left falces respectively. The distance between the two falces was 3.2, 4.5 and 7.8 mm at their proximal, middle and distal thirds. An accessory small falx (31.8 × 2 mm) was also found approximately 3.4 mm lateral to the right falx cerebelli and blended with the lateral surface of the right falx cerebelli. There was only one occipital venous sinus (diameter, 2.5 mm) and no marginal sinus was detected. At the right floor of the posterior cranial fossa (posterolateral to the foramen magnum) an additional dural venous sinus was found, which connected the terminal portion of the right sigmoid sinus to the occipital and right transverse sinuses via one medial and two lateral branches respectively. We believe that such a complex dural-venous variation in the posterior cranial fossa has not previously been reported. Neurosurgeons and neuroradiologists should be aware of such variations, as these could be potential sources of haemorrhage during suboccipital approaches or may lead to erroneous interpretations of imaging of the posterior cranial fossa

Aspects of Housing Development analysis of the impacts of social & economic issues on housing physical indicators (Case Study: The 2nd District of Tehran)

Housing development and the planning of it includes variant aspects, which are important to study, in order to have a successful plan in a city. Physical aspect contains scrutiny of seeming and objective factors of housing and dwellings, which includes kinds of building materials, quality of structure, urban accesses, and etc. Social aspect contains issues such as structure of population and household, cultural issues and etc. And economic aspect of housing include issues like cost of dwellings and real states, households’ incomes and etc. In addition, these aspects have influences on each other too. For example making changes in social and economic conditions will cause the change of physic of housing. Therefore, this paper studies impacts of social and economic situation on physic of housing in the 2nd District of Tehran as a bipolar area (in north and south of Hemmat expressway) which suffers a serious inequality in distribution of services and facilities, households’ income, cost of properties, cultural and social indicators and etc. So the relationship between physical aspect of housing and social and economic factors will be defined as a function by the two fallowing method: Factor-Analysis and Regression. This paper concludes that enhance of quality of housing is not achievable whit physical intervention merely and a comprehensive approach is necessary for housing planning

Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Previous functional magnetic resonance imaging (fMRI) studies have shown that a subgroup of patients diagnosed as being in a vegetative state are aware and able to communicate by performing a motor imagery task in response to commands. Due to the fMRI\u27s cost and accessibility, there is a need for exploring different imaging modalities that can be used at the bedside. A promising technique is functional near infrared spectroscopy (fNIRS) that has been successfully applied to measure brain oxygenation in humans. Due to the limited depth sensitivity of continuous-wave NIRS, time-resolved (TR) detection has been proposed as a way of enhancing the sensitivity to the brain, since late arriving photons have a higher probability of reaching the brain. The goal of this study was to assess the feasibility and sensitivity of TR fNIRS in detecting brain activity during motor imagery. Fifteen healthy subjects were recruited in this study, and the fNIRS results were validated using fMRI. The change in the statistical moments of the distribution of times of flight (number of photons, mean time of flight and variance) were calculated for each channel to determine the presence of brain activity. The results indicate up to an 86% agreement between fMRI and TR-fNIRS and the sensitivity ranging from 64 to 93% with the highest value determined for the mean time of flight. These promising results highlight the potential of TR-fNIRS as a portable brain computer interface for patients with disorder of consciousness

Deep Sequential Models for Task Satisfaction Prediction

Detecting and understanding implicit signals of user satisfaction are essential for experimentation aimed at predicting searcher satisfaction. As retrieval systems have advanced, search tasks have steadily emerged as accurate units not only to capture searcher's goals but also in understanding how well a system is able to help the user achieve that goal. However, a major portion of existing work on modeling searcher satisfaction has focused on query level satisfaction. The few existing approaches for task satisfaction prediction have narrowly focused on simple tasks aimed at solving atomic information needs. In this work we go beyond such atomic tasks and consider the problem of predicting user's satisfaction when engaged in complex search tasks composed of many different queries and subtasks. We begin by considering holistic view of user interactions with the search engine result page (SERP) and extract detailed interaction sequences of their activity. We then look at query level abstraction and propose a novel deep sequential architecture which leverages the extracted interaction sequences to predict query level satisfaction. Further, we enrich this model with auxiliary features which have been traditionally used for satisfaction prediction and propose a unified multi-view model which combines the benefit of user interaction sequences with auxiliary features. Finally, we go beyond query level abstraction and consider query sequences issued by the user in order to complete a complex task, to make task level satisfaction predictions. We propose a number of functional composition techniques which take into account query level satisfaction estimates along with the query sequence to predict task level satisfaction. Through rigorous experiments, we demonstrate that the proposed deep sequential models significantly outperform established baselines at both query and task satisfaction prediction. Our findings have implications on metric development for gauging user satisfaction and on designing systems which help users accomplish complex search tasks