User requirement elicitation for cross-language information retrieval

Who are the users of a cross-language retrieval system? Under what circumstances do they need to perform such multi-language searches? How will the task and the context of use affect successful interaction with the system? Answers to these questions were explored in a user study performed as part of the design stages of Clarity, a EU founded project on cross-language information retrieval. The findings resulted in a rethink of the planned user interface and a consequent expansion of the set of services offered. This paper reports on the methodology and techniques used for the elicitation of user requirements as well as how these were in turn transformed into new design solutions

save to DISC: Documenting Innovation in Music Learning

The paper discusses an approach to determining the worth and value of innovation in music education and measuring it’s capacity for meaning and engagement. It also aims to identify new examples of innovation across a broad range of music learning contexts and establish a rigorous digital process for documenting, evaluating and distributing innovative cases and resources for present and future contexts. It discusses specifically a pilot project that seeks to document innovation in sound curriculum (DISC). save to DISC is an exploratory study in an Australasian CRC for Interaction Design (ACID) project that proposes to establish flexible and effective procedures for the sourcing, evaluating, refereeing, editing, producing, validating, storing, publishing, and distributing of a wide range of media and content types. It involves documenting innovative and successful practice in music education, creating and evaluating programs in difficult/challenging school contexts and commissioning and encouraging the production of resource materials for 21 st century contexts

Knowledge will Propel Machine Understanding of Content: Extrapolating from Current Examples

Machine Learning has been a big success story during the AI resurgence. One particular stand out success relates to learning from a massive amount of data. In spite of early assertions of the unreasonable effectiveness of data, there is increasing recognition for utilizing knowledge whenever it is available or can be created purposefully. In this paper, we discuss the indispensable role of knowledge for deeper understanding of content where (i) large amounts of training data are unavailable, (ii) the objects to be recognized are complex, (e.g., implicit entities and highly subjective content), and (iii) applications need to use complementary or related data in multiple modalities/media. What brings us to the cusp of rapid progress is our ability to (a) create relevant and reliable knowledge and (b) carefully exploit knowledge to enhance ML/NLP techniques. Using diverse examples, we seek to foretell unprecedented progress in our ability for deeper understanding and exploitation of multimodal data and continued incorporation of knowledge in learning techniques.Comment: Pre-print of the paper accepted at 2017 IEEE/WIC/ACM International Conference on Web Intelligence (WI). arXiv admin note: substantial text overlap with arXiv:1610.0770

Closing the loop: assisting archival appraisal and information retrieval in one sweep

In this article, we examine the similarities between the concept of appraisal, a process that takes place within the archives, and the concept of relevance judgement, a process fundamental to the evaluation of information retrieval systems. More specifically, we revisit selection criteria proposed as result of archival research, and work within the digital curation communities, and, compare them to relevance criteria as discussed within information retrieval's literature based discovery. We illustrate how closely these criteria relate to each other and discuss how understanding the relationships between the these disciplines could form a basis for proposing automated selection for archival processes and initiating multi-objective learning with respect to information retrieval

Potentials of social media for tacit knowledge sharing amongst physicians : preliminary findings

Tacit knowledge sharing amongst physicians, such as the sharing of clinical experiences, skills, or know-how, or know-whom, is known to have a significant impact on the quality of medical diagnosis and decisions. This paper posits that social media can provide new opportunities for tacit knowledge sharing amongst physicians, and demonstrates this by presenting findings from a review of relevant literature and a survey conducted with physicians. Semi-structured interviews were conducted with ten physicians from around the world who were active users of social media. Initial thematic analysis revealed eight themes as potential contributions of social web tools to facilitate tacit knowledge flow amongst physicians. The emergent themes are defined, linked to the literature, and supported by instances of interview transcripts. Findings presented here are preliminary, and final results will be reported after accomplishing all phases of data collection and analysis