Towards better measures: evaluation of estimated resource description quality for distributed IR

An open problem for Distributed Information Retrieval systems (DIR) is how to represent large document repositories, also known as resources, both accurately and efficiently. Obtaining resource description estimates is an important phase in DIR, especially in non-cooperative environments. Measuring the quality of an estimated resource description is a contentious issue as current measures do not provide an adequate indication of quality. In this paper, we provide an overview of these currently applied measures of resource description quality, before proposing the Kullback-Leibler (KL) divergence as an alternative. Through experimentation we illustrate the shortcomings of these past measures, whilst providing evidence that KL is a more appropriate measure of quality. When applying KL to compare different QBS algorithms, our experiments provide strong evidence in favour of a previously unsupported hypothesis originally posited in the initial Query-Based Sampling work

Freedom and Restraint: Tags, Vocabularies and Ontologies

The benefit of metadata is widely recognized. However, the nature of that information and the method of production remains a topic of some debate. This division is most noticeable between those who believe in ’free tagging’, and those who prefer the more formal construction of an ontology to define both the vocabulary of the domain and the relationships between the concepts within it. Looking at the community surrounding online amateur authors and the descriptive metadata they have developed over the last thirty years we consider what we can learn from a mature but amateur tagging community. This paper considers how these two systems might be used together to add the easy usability of free tagging to ontology descriptions and the conceptual richness of ontologies to free tags

How to promote knowledge sharing in cross-functional NPD teams

This paper investigates the common issues that may arise in cross-functional new product development (NPD) teams from a Knowledge Management perspective. The study has been built around a contextualized trigger, where several factors were preventing a new-born NPD team from performing effectively. The purpose of this paper is to give insights of the main dynamics involved in the knowledge sharing process throughout the application of a systematic problem-solving approach to the case investigated by the authors. Due to the impossibility of building a universal recipe suitable for every team in every situation, this work represents a compromise trying to exemplify how to prioritise interventions in a given context, in order to provide a benchmark for similar circumstances. This paper, using an action research method within a single case context, takes shape around the advises and suggestions made by authors to Electronic Connected Ltd (disguised name), a small-medium enterprise (SME) in a situation of NPD paralysis. In particular, the paper emphasizes the importance of effective leadership and supporting environment in facilitating communication, enhancing cohesiveness, fostering joint commitment and giving direction in order to enable knowledge sharing and to leverage capabilities to conclusively deliver new products

Mental disorders on online social media through the lens of language and behaviour:Analysis and visualisation

Due to the worldwide accessibility to the Internet along with the continuous advances in mobile technologies, physical and digital worlds have become completely blended, and the proliferation of social media platforms has taken a leading role over this evolution. In this paper, we undertake a thorough analysis towards better visualising and understanding the factors that characterise and differentiate social media users affected by mental disorders. We perform different experiments studying multiple dimensions of language, including vocabulary uniqueness, word usage, linguistic style, psychometric attributes, emotions' co-occurrence patterns, and online behavioural traits, including social engagement and posting trends. Our findings reveal significant differences on the use of function words, such as adverbs and verb tense, and topic-specific vocabulary, such as biological processes. As for emotional expression, we observe that affected users tend to share emotions more regularly than control individuals on average. Overall, the monthly posting variance of the affected groups is higher than the control groups. Moreover, we found evidence suggesting that language use on micro-blogging platforms is less distinguishable for users who have a mental disorder than other less restrictive platforms. In particular, we observe on Twitter less quantifiable differences between affected and control groups compared to Reddit.Comment: To appear in Elsevier Information Processing & Managemen

Analysing Lexical Semantic Change with Contextualised Word Representations

This paper presents the first unsupervised approach to lexical semantic change that makes use of contextualised word representations. We propose a novel method that exploits the BERT neural language model to obtain representations of word usages, clusters these representations into usage types, and measures change along time with three proposed metrics. We create a new evaluation dataset and show that the model representations and the detected semantic shifts are positively correlated with human judgements. Our extensive qualitative analysis demonstrates that our method captures a variety of synchronic and diachronic linguistic phenomena. We expect our work to inspire further research in this direction.Comment: To appear in Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (ACL-2020

Kanembu-Kanuri relationship: a proposal

The paper takes recourse to oral tradition and linguistics to ascertain the assertion that the presentday Kanuri and Kanembu speech forms emerged from the same parent language. In determining the parent language, the descriptions of the various components (i.e. clans and ethnic groups) of Kanuri and Kanembu are given as a first basis and the relation of each dialect of Kanuri and Kanembu to the other (i.e. dialect contiguity) is demonstrated as a second basis. Taking into consideration the sociolinguistic background of both Kanuri and Kanembu, the brief history of their divergence, the strong contention of the Borno Ulama and the dialect contiguity of the data presented, the paper concludes that Kanuri and Kanembu are initially one and the same language with ancient classical Kanembu being the parent language

Role of sentiment classification in sentiment analysis: a survey

Through a survey of literature, the role of sentiment classification in sentiment analysis has been reviewed. The review identifies the research challenges involved in tackling sentiment classification. A total of 68 articles during 2015 – 2017 have been reviewed on six dimensions viz., sentiment classification, feature extraction, cross-lingual sentiment classification, cross-domain sentiment classification, lexica and corpora creation and multi-label sentiment classification. This study discusses the prominence and effects of sentiment classification in sentiment evaluation and a lot of further research needs to be done for productive results

Mapping the Evolution of "Clusters": A Meta-analysis

This paper presents a meta-analysis of the “cluster literature” contained in scientific journals from 1969 to 2007. Thanks to an original database we study the evolution of a stream of literature which focuses on a research object which is both a theoretical puzzle and an empirical widespread evidence. We identify different growth stages, from take-off to development and maturity. We test the existence of a life-cycle within the authorships and we discover the existence of a substitutability relation between different collaborative behaviours. We study the relationships between a “spatial” and an “industrial” approach within the textual corpus of cluster literature and we show the existence of a “predatory” interaction. We detect the relevance of clustering behaviours in the location of authors working on clusters and in measuring the influence of geographical distance in co-authorship. We measure the extent of a convergence process of the vocabulary of scientists working on clusters.Cluster, Life-Cycle, Cluster Literature, Textual Analysis, Agglomeration, Co-Authorship