Good Applications for Crummy Entity Linkers? The Case of Corpus Selection in Digital Humanities

Over the last decade we have made great progress in entity linking (EL) systems, but performance may vary depending on the context and, arguably, there are even principled limitations preventing a "perfect" EL system. This also suggests that there may be applications for which current "imperfect" EL is already very useful, and makes finding the "right" application as important as building the "right" EL system. We investigate the Digital Humanities use case, where scholars spend a considerable amount of time selecting relevant source texts. We developed WideNet; a semantically-enhanced search tool which leverages the strengths of (imperfect) EL without getting in the way of its expert users. We evaluate this tool in two historical case-studies aiming to collect a set of references to historical periods in parliamentary debates from the last two decades; the first targeted the Dutch Golden Age, and the second World War II. The case-studies conclude with a critical reflection on the utility of WideNet for this kind of research, after which we outline how such a real-world application can help to improve EL technology in general.Comment: Accepted for presentation at SEMANTiCS '1

The role of knowledge in determining identity of long-tail entities

The NIL entities do not have an accessible representation, which means that their identity cannot be established through traditional disambiguation. Consequently, they have received little attention in entity linking systems and tasks so far. Given the non-redundancy of knowledge on NIL entities, the lack of frequency priors, their potentially extreme ambiguity, and numerousness, they form an extreme class of long-tail entities and pose a great challenge for state-of-the-art systems. In this paper, we investigate the role of knowledge when establishing the identity of NIL entities mentioned in text. What kind of knowledge can be applied to establish the identity of NILs? Can we potentially link to them at a later point? How to capture implicit knowledge and fill knowledge gaps in communication? We formulate and test hypotheses to provide insights to these questions. Due to the unavailability of instance-level knowledge, we propose to enrich the locally extracted information with profiling models that rely on background knowledge in Wikidata. We describe and implement two profiling machines based on state-of-the-art neural models. We evaluate their intrinsic behavior and their impact on the task of determining identity of NIL entities

Conversational artificial intelligence - demystifying statistical vs linguistic NLP solutions

yesThis paper aims to demystify the hype and attention on chatbots and its association with conversational artificial intelligence. Both are slowly emerging as a real presence in our lives from the impressive technological developments in machine learning, deep learning and natural language understanding solutions. However, what is under the hood, and how far and to what extent can chatbots/conversational artificial intelligence solutions work – is our question. Natural language is the most easily understood knowledge representation for people, but certainly not the best for computers because of its inherent ambiguous, complex and dynamic nature. We will critique the knowledge representation of heavy statistical chatbot solutions against linguistics alternatives. In order to react intelligently to the user, natural language solutions must critically consider other factors such as context, memory, intelligent understanding, previous experience, and personalized knowledge of the user. We will delve into the spectrum of conversational interfaces and focus on a strong artificial intelligence concept. This is explored via a text based conversational software agents with a deep strategic role to hold a conversation and enable the mechanisms need to plan, and to decide what to do next, and manage the dialogue to achieve a goal. To demonstrate this, a deep linguistically aware and knowledge aware text based conversational agent (LING-CSA) presents a proof-of-concept of a non-statistical conversational AI solution

Knowledge-Driven Implicit Information Extraction

Natural language is a powerful tool developed by humans over hundreds of thousands of years. The extensive usage, flexibility of the language, creativity of the human beings, and social, cultural, and economic changes that have taken place in daily life have added new constructs, styles, and features to the language. One such feature of the language is its ability to express ideas, opinions, and facts in an implicit manner. This is a feature that is used extensively in day to day communications in situations such as: 1) expressing sarcasm, 2) when trying to recall forgotten things, 3) when required to convey descriptive information, 4) when emphasizing the features of an entity, and 5) when communicating a common understanding. Consider the tweet New Sandra Bullock astronaut lost in space movie looks absolutely terrifying and the text snippet extracted from a clinical narrative He is suffering from nausea and severe headaches. Dolasteron was prescribed . The tweet has an implicit mention of the entity Gravity and the clinical text snippet has implicit mention of the relationship between medication Dolasteron and clinical condition nausea . Such implicit references of the entities and the relationships are common occurrences in daily communication and they add value to conversations. However, extracting implicit constructs has not received enough attention in the information extraction literature. This dissertation focuses on extracting implicit entities and relationships from clinical narratives and extracting implicit entities from Tweets. When people use implicit constructs in their daily communication, they assume the existence of a shared knowledge with the audience about the subject being discussed. This shared knowledge helps to decode implicitly conveyed information. For example, the above Twitter user assumed that his/her audience knows that the actress Sandra Bullock starred in the movie Gravity and it is a movie about space exploration. The clinical professional who wrote the clinical narrative above assumed that the reader knows that Dolasteron is an anti-nausea drug. The audience without such domain knowledge may not have correctly decoded the information conveyed in the above examples. This dissertation demonstrates manifestations of implicit constructs in text, studies their characteristics, and develops a software solution that is capable of extracting implicit information from text. The developed solution starts by acquiring relevant knowledge to solve the implicit information extraction problem. The relevant knowledge includes domain knowledge, contextual knowledge, and linguistic knowledge. The acquired knowledge can take different syntactic forms such as a text snippet, structured knowledge represented in standard knowledge representation languages such as the Resource Description Framework (RDF) or other custom formats. Hence, the acquired knowledge is pre-processed to create models that can be processed by machines. Such models provide the infrastructure to perform implicit information extraction. This dissertation focuses on three different use cases of implicit information and demonstrates the applicability of the developed solution in these use cases. They are: 1) implicit entity linking in clinical narratives, 2) implicit entity linking in Twitter, and 3) implicit relationship extraction from clinical narratives. The evaluations are conducted on relevant annotated datasets for implicit information and they demonstrate the effectiveness of the developed solution in extracting implicit information from text

Dynamic behavior-based control and world-embedded knowledge for interactive artificial intelligence

Video game designers depend on artificial intelligence to drive player experience in modern games. Therefore it is critical that AI not only be fast and computation- ally inexpensive, but also easy to incorporate with the design process. We address the problem of building computationally inexpensive AI that eases the game de- sign process and provides strategic and tactical behavior comparable with current industry-standard techniques. Our central hypothesis is that behavior-based characters in games can exhibit effec- tive strategy and coordinate in teams through the use of knowledge embedded in the world and a new dynamic approach to behavior-based control that enables charac- ters to transfer behavioral knowledge. We use dynamic extensions for behavior-based subsumption and world-embedded knowledge to simplify and enhance game character intelligence. We find that the use of extended affordances to embed knowledge in the world can greatly reduce the effort required to build characters and AI engines while increasing the effectiveness of the behavior controllers. In addition, we find that the technique of multi-character affordances can provide a simple mechanism for enabling team coordination. We also show that reactive teaming, enabled by dynamic extensions to the subsumption architecture, is effective in creating large adaptable teams of characters. Finally, we show that the command policy for reactive teaming can be used to improve performance of reactive teams for tactical situations

Ensimmäinen ja toinen käsikirjoitusversio väitöskirjaa varten

This publication contains the first and the second manuscript version for LauriLahti’s doctoral dissertation in 2015 "Computer-assisted learning based on cumulative vocabularies, conceptual networks and Wikipedia linkage".Tämä julkaisu sisältää ensimmäisen ja toisen käsikirjoitusversion Lauri Lahden väitöskirjaan vuonna 2015 "Tietokoneavusteinen oppiminen perustuen karttuviin sanastoihin, käsiteverkostoihin ja Wikipedian linkitykseen".Not reviewe

Smart Mobility Cities: Connecting Bristol and Kuala Lumpur project report

Financed by the British Council Institutional Links program this Smart Mobility Cities project has opened a fascinating window on a journey of discovery linking Bristol and Kuala Lumpur. This journey was in part directed towards the realisation of Smart Mobility solutions to the socio-economic and environmental challenges of global urbanisation. Beyond this, the journey was also concerned to strengthen research and innovation partnerships between the UK and the emerging knowledge economy of Malaysia, enabling UK social scientists to collaborate on challenging global issues with international researchers and vice versa. This Smart Mobility Cities project report presents innovative, creative and yet fully practical solutions for these societal challenges. Solutions that explore a range of opportunities, whichinclude those arising from new urban governance requirements, and which are in-line with visions for sustainable urban mobility.These Smart Mobility solutions have arisen from intensive co-design and co-creation engagement with a diversity of stakeholders. Research co-production has linked the principal university partners of the University of the West of England (UWE), Bristol, and Taylor’sUniversity, Kuala Lumpur, together with the Malaysia Institute of Transport (MITRANS), Universiti Teknologi Mara, and the University Sains Malaysia (USM) in intensive engagement with stakeholder interests in both UK and Malaysia over a two-year period

Combining content-based and EAP approaches to academic writing: Towards an eclectic program

Over the past decade, Australian universities have experienced an exponential increase in the enrolment of fee-paying overseas students whose preparation for tertiary studies may differ significantly from that of local students. Despite English language proficiency requirements, there is some concern that international entry tests do not adequately measure the complex features of university writing; an important concern given that student success is heavily dependent on their mastery of academic writing. As a result, many international students require additional support structures. Until the present, debate about the most effective way to meet the diverse needs of English as an Additional Language (EAL) writers entering universities has concerned a choice between two alternatives: on one hand a separate, short-term English for Academic Purposes (EAP) language program and on the other, direct entry into disciplines with lecturers taking responsibility for assisting students to learn the discipline-specific language skills required. While the Australian Universities Quality Agency (AUQA, 2009, 2013) supports the latter view, this research investigates a third alternative; that is, an English for Academic Purposes Pathway program (EAPP) that not only teaches general academic English skills, but also English required in discipline specific contexts, as well as important and necessary adjunct skills that support writing. This three-phase, mixed-methods study used both qualitative and quantitative data to investigate the efficacy of such a program. The study, which was analytic, descriptive and comparative in approach, was conducted in a naturalistic setting and, where possible, qualitative data were used to support the findings from quantitative data. Theoretical propositions guided the data collection and provided important links to connect primary and secondary research. Phase 1 investigated the academic writing needs perceived by 60 students who were either studying in the 20-week or 10-week EAPP program at Swan University (a pseudonym). Perceptions of student needs by 13 EAPP teachers were also analysed and writing samples collected. In Phase 2, the cohort decreased to 31 students representing seven faculties. Perceptions of 17 faculty staff from across and within these seven faculties were sought regarding the tasks and genres required for EAL students to meet the writing expectations within these disciplines. The marked ex-EAPP student’s faculty writing assignments were collected and analysed at the end of first semester. At this stage, because the volume of student writing produced over the course of the study was so large, disproportional stratified random sampling was used to select and analyse the EAPP and faculty writing of a sample of seven students. Research by Kaldor, Herriman and Rochecouste (1998) provided direction for frame analysis which was used to analyse the student writing. In Phase 3, which was conducted one year after entering their chosen faculties, 22 students replied to a request to judge which, if any, writing skills from their EAPP program had transferred to assist them with their faculty writing. Findings are discussed in relation to four major issues. Firstly, reflections provided by ex-EAPP students ascertained that, on entering the EAPP program, the majority of them had been academically, linguistically, culturally and socially unprepared for study at master’s degree level in an Australian university. Secondly, analysis determined that in the students’ first year of faculty study, writing tasks and genres were almost identical in type, complexity and word-count restrictions to those taught in the EAPP program and that students readily adapted to the highly specified frameworks of any tasks that were unfamiliar. A third major finding was the significance that students placed on the type of feedback necessary to support their writing. Finally, students identified major areas of improvement in their academic writing at the end of the program, but provided suggestions in key pedagogical areas about how the EAPP program could be improved to better address their needs. This study found that EAL writing development involves much more than content knowledge, mastery over discipline-specific genre requirements and a wide vocabulary. Academic writing comprises a complex combination of extratextual, circumtextual, intratextual and intertextual features and skills, some of which are completely new to international students. A model was proposed to illustrate elements that provide: circumtextual assistance for prewriting support; intertextual assistance through reading and writing support; extratextual assistance through sociocultural support, and intratextual assistance through the scaffolding of academic writing skills. To conclude, recommended modifications to the program are presented

Project Risk Assessment and Corporate Behavior: Creating Knowledge for Sustainable Business

In a VUCA world (volatile, uncertain, complex, and ambiguous), organizations, in order to achieve a sustainable competitive advantage, must learn to mitigate risk and prioritize performance and innovation. In the last decade, as a way to respond to market demands, projects emerge as a way for organizations to implement their strategic objectives in order to respond to a need, opportunity, or threat in an efficient way. This e-book includes a collection of 11 papers that discuss theoretical approaches and case studies, focused on a combined effect between Project Risk Assessment and corporate behaviour in order to support the sustainability and business resilience in a competitive environment. The e-book will be of particular interest to entrepreneurs, researchers, and policymakers