The structure of verbal sequences analyzed with unsupervised learning techniques

Data mining allows the exploration of sequences of phenomena, whereas one usually tends to focus on isolated phenomena or on the relation between two phenomena. It offers invaluable tools for theoretical analyses and exploration of the structure of sentences, texts, dialogues, and speech. We report here the results of an attempt at using it for inspecting sequences of verbs from French accounts of road accidents. This analysis comes from an original approach of unsupervised training allowing the discovery of the structure of sequential data. The entries of the analyzer were only made of the verbs appearing in the sentences. It provided a classification of the links between two successive verbs into four distinct clusters, allowing thus text segmentation. We give here an interpretation of these clusters by applying a statistical analysis to independent semantic annotations

Norm Based Causal Reasoning in Textual Corpus

Truth based entailments are not sufficient for a good comprehension of NL. In fact, it can not deduce implicit information necessary to understand a text. On the other hand, norm based entailments are able to reach this goal. This idea was behind the development of Frames (Minsky 75) and Scripts (Schank 77, Schank 79) in the 70's. But these theories are not formalized enough and their adaptation to new situations is far from being obvious. In this paper, we present a reasoning system which uses norms in a causal reasoning process in order to find the cause of an accident from a text describing it

Human Performance Contributions to Safety in Commercial Aviation

In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that contribute to routine successful outcomes, safety management and system design decisions are based on a small sample of non- representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant and largely unrecognized risk when making policy decisions about human roles and responsibilities. Opportunities exist to leverage the vast amount of data that has already been collected, or could be easily obtained, to increase our understanding of human contributions to things going right in commercial aviation. The principal focus of this assessment was to identify current gaps and explore methods for identifying human success data generated by the aviation system, from personnel and within the supporting infrastructure

Review of current practices in recording road traffic incident data: with specific reference to spatial analysis and road policing policy

Road safety involves three major components: the road system, the human factor and the vehicle element. These three elements are inter-linked through geo-referenced traffic events and provide the basis for road safety analyses and attempts to reduce the number of road traffic incidents and improve road safety. Although numbers of deaths and serious injuries are back to approximately the 1950s levels when there were many fewer vehicles on the road, there are still over 100 fatalities or serious injuries every day, and this is a considerable waste of human capital. It is widely acknowledged that the location perspective is the most suitable methodology by which to analyse different traffic events, where by in this paper, I will concentrating on the relationship between road traffic incidents and traffic policing. Other methods include studying road and vehicle engineering and these will be discussed later. It is worth noting here that there is some division within the literature concerning the definitions of ‘accident’ and ‘incident’. In this paper I will use ‘incident’ because it is important to acknowledge a vast majority of ‘road accidents’ are in fact crimes. However I will use the term ‘accident’ where it is referred to in the literature or relevant reports. It is important to mention here that a road traffic accident can be defined as ‘the product of an unwelcome interaction between two or more moving objects, or a fixed and moving object’ (Whitelegg 1986). Road safety and road incident reduction relates to many other fields of activity including education, driver training, publicity campaigns, police enforcement, road traffic policing, the court system, the National Health Service and Vehicle engineering. Although the subject of using GIS to analyse road traffic incidents has not received much academic attention, it lies in the field of crime mapping which is becoming increasingly important. It is clear that studies have been attempted to analyse road traffic incidents using GIS are increasingly sophisticated in terms of hypotheses and statistical technique (for example see Austin, Tight and Kirby 1997). However it is also clear that there is considerable blurring of boundaries and the analysis of road accidents sits uncomfortably in crime mapping. This is due to four main reasons: - Road traffic incidents are associated with road engineering, which is concerned with generic solutions while road traffic analysis is about sensitivity to particular contexts. - Not all road traffic incidents are crimes - It is not just the police who have an interest in reducing road traffic incidents, other partners include local authorities, hospitals and vehicle manufacturers - The management of road traffic incidents is not just confined to the police GIS has been used for over thirty years however it has only been recently been used in the field of transportation. The field of transportation has come to embrace Geographical Information Systems as a keytechnology to support its research and operational need. The acronym GIS-T is often employed to refer to the application and adaptation of GIS to research, planning and management in transportation. GIS-T covers a broad arena of disciplines of which road traffic incident detection is just one theme. Others include in vehicle navigation systems. Initially it was only used to ask simple accident enquiries such as depicting the relative incidence of accidents in wet weather or when there is no street lighting, or to flag high absolute or relative incidences of accidents (see Anderson 2002). Recently however there has been increased acknowledgement that there is a requirement to go beyond these simple questions and to extend the analyses. It has been widely claimed by academics and the police alike that knowing where road accidents occur must lead to better road policing, in order to ensure that road policing becomes better integrated with other policing activities. This paper will be used to explore issues surrounding the analysis of road traffic accidents and how GIS analysts, police and policy makers can achieve a better understanding of road traffic incidents and how to reduce them. For the purpose of this study I will be trying to achieve a broader overview of the aspects concerning road accident analysis with a strong emphasis on data quality and accuracy with concern to GIS analysis. Data quality and accuracy are seen as playing a pivotal role in the road traffic management agenda because they assist the police and Local Authorities as to the specific location whereby management can be undertaken. Part one will consider the introduction to road incidents and their relationship with geography and spatial analysis and how this were initially applied to locating ‘hotspots’ and the more recent theory of ‘accident migration’. Part two will address current data issues of the UK collection procedure. This section will pay particular reference to geo-referencing and the implication of data quality on the procedure of analysing road incidents using GIS. Part three addresses issues surrounding the spatial analysis of road traffic incidents, including some techniques such as spatial autocorrelation, time-space geography and the modifiable area unit problem. Finally part four looks at the role of effective road traffic policing and how this can be achieved due to better understanding of the theory and issues arising from analysing road traffic incidents. It will also look at the diffusion and use of GIS within the police and local authorities

About Norms and Causes

Knowing the norms of a domain is crucial, but there exist no repository of norms. We propose a method to extract them from texts: texts generally do not describe a norm, but rather how a state-of-affairs differs from it. Answers concerning the cause of the state-of-affairs described often reveal the implicit norm. We apply this idea to the domain of driving, and validate it by designing algorithms that identify, in a text, the "basic" norms to which it refers implicitly

Retraction with face saving: Modelling conversational interaction through dynamic hypermedia

This paper describes RWFS (Retraction With Face Saving), a hypermedia application which models an interview between a lawyer and his client ‐ a lorry driver ‐ facing court charges of reckless driving. At one level RWFS takes the form of a sophisticated game in which different outcomes to the interview are possible according to the learner's degree of skill. At another level, RWFS is designed to encourage the language learner's awareness and understanding of the pragmatic features of conversation. RWFS runs on HyperContext, a hybrid hypertextlexpert system developed in Pavia by two of the authors, Marco Piastra and Roberto Bolognesi, and which supports dynamic hypermedia units. HyperContext's dynamic linking capacity plays a vital role in simulating significant conversational features such as the conditioning of a current move in the conversation by information acquired much earlier in the course of the interview. In this connection, the paper discusses the contribution of RMCI (Re‐usable Model of Conversational Interaction), a re‐usable application‐independent applied model of interaction on which the game is based, and which links a tactical level (the conversation) to a metalevel which provides a move‐by‐move commentary on interactional theory. In its turn, RMCFs metalevel is linked to a strategic level which interprets the structure of the conversation in terms of a pyramid‐like hierarchy of increasingly abstract theoretical concepts

Event detection, tracking, and visualization in Twitter: a mention-anomaly-based approach

The ever-growing number of people using Twitter makes it a valuable source of timely information. However, detecting events in Twitter is a difficult task, because tweets that report interesting events are overwhelmed by a large volume of tweets on unrelated topics. Existing methods focus on the textual content of tweets and ignore the social aspect of Twitter. In this paper we propose MABED (i.e. mention-anomaly-based event detection), a novel statistical method that relies solely on tweets and leverages the creation frequency of dynamic links (i.e. mentions) that users insert in tweets to detect significant events and estimate the magnitude of their impact over the crowd. MABED also differs from the literature in that it dynamically estimates the period of time during which each event is discussed, rather than assuming a predefined fixed duration for all events. The experiments we conducted on both English and French Twitter data show that the mention-anomaly-based approach leads to more accurate event detection and improved robustness in presence of noisy Twitter content. Qualitatively speaking, we find that MABED helps with the interpretation of detected events by providing clear textual descriptions and precise temporal descriptions. We also show how MABED can help understanding users' interest. Furthermore, we describe three visualizations designed to favor an efficient exploration of the detected events.Comment: 17 page

Manuscript contexts and the transmission of the Agnus Castus herbal in MS Sloane 3160

MS Sloane 3160 is a miscellaneous volume containing one copy of the herbal Agnus Castus in Middle English. Traditionally, editions focused on texts in isolation and did not look in detail to the rest of the material, diminishing the potential of manuscript contexts in explaining how texts flow and are received by a specific audience. If we consider these groupings of texts a collective product in which all the co-texts are part of an internal dialogue, the importance of looking at the whole volume from a collective perspective becomes paramount in understanding the final aim of the compiler, and the processes of transmission of text and/or texts. The objective of this article has been to study the arrangement of the material contained in MS Sloane 3160 as a starting point to frame future comparison with manuscripts containing the same herbal. The results point to the identification of patterns which would confirm the “anthologistic impulse” (Lerer 2000). The structure of this manuscript would contain a spectrum of the most important areas that would cover the contents of a typical vademecum of the time, including religious texts, but more studies are needed in order to be able to assess these contexts in medical miscellanies. The impact and transmission of the Agnus Castus herbal needs to be studied collectively, and assessing the manuscript contexts in which the text is naturally embedded points to the right direction in understanding all the processes therein