Road segment identification in natural language text

This paper describes a technique to extract geographic location information from a natural language description of a location. The technique relies on a set of domain specific tags and a set of keywords. The tags are used to identify roads, intersections, and landmarks. Tag combinations are used to discover road segments. The technique is applied to understanding highway construction reports for the Canadian Province of Ontario.IFIP International Conference on Artificial Intelligence in Theory and Practice - Speech and Natural LanguageRed de Universidades con Carreras en Informática (RedUNCI

Road segment identification in natural language text

This paper describes a technique to extract geographic location information from a natural language description of a location. The technique relies on a set of domain specific tags and a set of keywords. The tags are used to identify roads, intersections, and landmarks. Tag combinations are used to discover road segments. The technique is applied to understanding highway construction reports for the Canadian Province of Ontario.IFIP International Conference on Artificial Intelligence in Theory and Practice - Speech and Natural LanguageRed de Universidades con Carreras en Informática (RedUNCI

Table-to-Text: Generating Descriptive Text for Scientific Tables from Randomized Controlled Trials

Unprecedented amounts of data have been generated in the biomedical domain, and the bottleneck for biomedical research has shifted from data generation to data management, interpretation, and communication. Therefore, it is highly desirable to develop systems to assist in text generation from biomedical data, which will greatly improve the dissemination of scientific findings. However, very few studies have investigated issues of data-to-text generation in the biomedical domain. Here I present a systematic study for generating descriptive text from tables in randomized clinical trials (RCT) articles, which includes: (1) an information model for representing RCT tables; (2) annotated corpora containing pairs of RCT table and descriptive text, and labeled structural and semantic information of RCT tables; (3) methods for recognizing structural and semantic information of RCT tables; (4) methods for generating text from RCT tables, evaluated by a user study on three aspects: relevance, grammatical quality, and matching. The proposed hybrid text generation method achieved a low bilingual evaluation understudy (BLEU) score of 5.69; but human review achieved scores of 9.3, 9.9 and 9.3 for relevance, grammatical quality and matching, respectively, which are comparable to review of original human-written text. To the best of our knowledge, this is the first study to generate text from scientific tables in the biomedical domain. The proposed information model, labeled corpora and developed methods for recognizing tables and generating descriptive text could also facilitate other biomedical and informatics research and applications

Transformer Neural Networks for Automated Story Generation

Towards the last two-decade Artificial Intelligence (AI) proved its use on tasks such as image recognition, natural language processing, automated driving. As discussed in the Moore’s law the computational power increased rapidly over the few decades (Moore, 1965) and made it possible to use the techniques which were computationally expensive. These techniques include Deep Learning (DL) changed the field of AI and outperformed other models in a lot of fields some of which mentioned above. However, in natural language generation especially for creative tasks that needs the artificial intelligent models to have not only a precise understanding of the given input, but an ability to be creative, fluent and, coherent within a content. One of these tasks is automated story generation which has been an open research area from the early days of artificial intelligence. This study investigates whether the transformer network can outperform state-of-the-art model for automated story generation. A large dataset gathered from Reddit’s WRITING PROMPTS sub forum and processed by the transformer network in order to compare the perplexity and two human evaluation metrics on transformer network and the state-of-the-art model. It was found that the transformer network cannot outperform the state-of-art model and even though it generated viable and novel stories it didn’t pay much attention to the prompts of the generated stories. Also, the results implied that there should be a better automated evaluation metric in order to assess the performance of story generation models

Hierarchical Graphs as Organisational Principle and Spatial Model Applied to Pedestrian Indoor Navigation

In this thesis, hierarchical graphs are investigated from two different angles – as a general modelling principle for (geo)spatial networks and as a practical means to enhance navigation in buildings. The topics addressed are of interest from a multi-disciplinary point of view, ranging from Computer Science in general over Artificial Intelligence and Computational Geometry in particular to other fields such as Geographic Information Science. Some hierarchical graph models have been previously proposed by the research community, e.g. to cope with the massive size of road networks, or as a conceptual model for human wayfinding. However, there has not yet been a comprehensive, systematic approach for modelling spatial networks with hierarchical graphs. One particular problem is the gap between conceptual models and models which can be readily used in practice. Geospatial data is commonly modelled - if at all - only as a flat graph. Therefore, from a practical point of view, it is important to address the automatic construction of a graph hierarchy based on the predominant data models. The work presented deals with this problem: an automated method for construction is introduced and explained. A particular contribution of my thesis is the proposition to use hierarchical graphs as the basis for an extensible, flexible architecture for modelling various (geo)spatial networks. The proposed approach complements classical graph models very well in the sense that their expressiveness is extended: various graphs originating from different sources can be integrated into a comprehensive, multi-level model. This more sophisticated kind of architecture allows for extending navigation services beyond the borders of one single spatial network to a collection of heterogeneous networks, thus establishing a meta-navigation service. Another point of discussion is the impact of the hierarchy and distribution on graph algorithms. They have to be adapted to properly operate on multi-level hierarchies. By investigating indoor navigation problems in particular, the guiding principles are demonstrated for modelling networks at multiple levels of detail. Complex environments like large public buildings are ideally suited to demonstrate the versatile use of hierarchical graphs and thus to highlight the benefits of the hierarchical approach. Starting from a collection of floor plans, I have developed a systematic method for constructing a multi-level graph hierarchy. The nature of indoor environments, especially their inherent diversity, poses an additional challenge: among others, one must deal with complex, irregular, and/or three-dimensional features. The proposed method is also motivated by practical considerations, such as not only finding shortest/fastest paths across rooms and floors, but also by providing descriptions for these paths which are easily understood by people. Beyond this, two novel aspects of using a hierarchy are discussed: one as an informed heuristic exploiting the specific characteristics of indoor environments in order to enhance classical, general-purpose graph search techniques. At the same time, as a convenient by- product of this method, clusters such as sections and wings can be detected. The other reason is to better deal with irregular, complex-shaped regions in a way that instructions can also be provided for these spaces. Previous approaches have not considered this problem. In summary, the main results of this work are: • hierarchical graphs are introduced as a general spatial data infrastructure. In particular, this architecture allows us to integrate different spatial networks originating from different sources. A small but useful set of operations is proposed for integrating these networks. In order to work in a hierarchical model, classical graph algorithms are generalised. This finding also has implications on the possible integration of separate navigation services and systems; • a novel set of core data structures and algorithms have been devised for modelling indoor environments. They cater to the unique characteristics of these environments and can be specifically used to provide enhanced navigation in buildings. Tested on models of several real buildings from our university, some preliminary but promising results were gained from a prototypical implementation and its application on the models

Cognitively-inspired direction giving

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2008.Includes bibliographical references (p. 133-140).Online mapping services and portable GPS units make it easy to get very detailed driving directions. While these directions are sufficient for an automaton to follow, they do not present a big picture description of the route. As a result, while people can follow these detailed turn-by-turn directions, it can be difficult for them to actually comprehend where they are going. Our goal is to make such directions more comprehensible. Our approach is to apply findings from human spatial cognition, the study of how people conceptualize and organize their knowledge of large-scale space, to create a system that generates written route overviews. Route overviews provide a big picture description of a route, and are intended to supplement the information in turn-by-turn directions. Our route overviews are based on cognitively-inspired design criteria such as: the use of spatial hierarchy, goal-directed descriptions, selective suppression of detail, and the use of the trunk segments and cognitive anchor points along the route. In our experiments, we show that we can make directions more comprehensible independent of the particular places a person knows - by using what we know about how people think about space to structure the way we present spatial information.by Gary Wai Keung Look.Ph.D

Personalized City Tours - An Extension of the OGC OpenLocation Specification

A business trip to London last month , a day visit in Cologne next saturday and romantic weekend in Paris in autumn – this example exhibits one of the central characteristics of today’s tourism. People in the western hemisphere take much pleasure in frequent and repeated short term visits of cities. Every city visitor faces the general problems of where to go and what to see in the diverse microcosm of a metropolis. This thesis presents a framework for the generation of personalized city tours - as extension of the Open Location Specification of the Open Geospatial Consortium. It is founded on context-awareness and personalization while at the same time proposing a combined approach to allow for adaption to the user. This framework considers TimeGeography and its algorithmic implementations to be able to cope with spatio-temporal constraints of a city tour. Traveling salesmen problems - for which a heuristic approache is proposed – are subjacent to the tour generation. To meet the requirements of today’s distributed and heterogeneous computing environments, the tour framework comprises individual services that expose standard-compliant interfaces and allow for integration in service oriented architectures

Enhancing the user-centred design of mobile location servies through the application of value

This thesis is concerned with the problem of designing Mobile Location Services (MLS) - also commonly termed Location-Based Services - that meet user needs. MLS are applications that users access via a portable device such as a mobile phone. They provide services (i.e. information or other functionality) to end-users based on knowledge of the location of individuals and other entities within the environment. The market failure of many mobile services, including MLS, has been attributed in part to failing to provide `value' to the end user. This thesis reviews different theoretical approaches to help understand the notion of `value', and how value may be used to inform design (Chapter 2). Research methods are also discussed, including the particular challenges with doing `mobile' research (Chapter 3). A survey of UK consumers( Chapter4 ) demonstratesa current lack of use, and lack of awarenesso f most forms of MLS in the UK. llowever, overall positive attitudes,a nd a range of behavioural and demographic data, suggest that MLS have the potential to be successful if they can be designed to meet user needs. A qualitative study of users' travelling behaviour (Chapter 5) then demonstrates how effective mobile information delivery can provide considerable value within a dynamic, uncertain and location-varying environment. This added value is highly dependent on contextual and situated factors, including existing information sources, variances in possible outcomes and the intrinsic qualities of information provision. The thesis then focuses on a particular application domain for MLS - drivers navigating in an unfamiliar environment. A literature review (Chapter 6) investigates how drivers navigate, and what their information needs are. Three experimental studies (Chapters 7 to 9) then investigate what information adds value within a navigation context, the impact of contextual influences on driving and navigation performance, and the impact of the quality of the navigation cue on task performance. Good landmarks (such as traffic lights) are shown to add value for drivers navigating an unfamiliar route, depending on the context at particular manoeuvres. This thesis discusses( Chapter 10) how a multi-disciplinary perspectivec an help maximise the acceptance and effectiveness of MLS. 'Value' can be used to design specific services for users, based on offering new freedoms to the individual within a mobile context, employing time and location sensitivity to maximise relevance, taking into account user knowledge, existing information sources and contextual factors, and ensuring impact on real-world outcomes. In conclusion (Chapter 11), specific contributions and avenues for future work are highlighted.EThOS - Electronic Theses Online ServiceGBUnited Kingdo