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Linguistic Fundamentals for Natural Language Processing II - Emily M. Bender - Bog - Springer International Publishing AG - Plusbog.dk

Muslim Fathers and Mistrusted Masculinity in Danish Schools - Anne Hovgaard Jorgensen - Bog - Springer International Publishing AG - Plusbog.dk

Visual Methods for Social Justice in Education - Laura Azzarito - Bog - Springer International Publishing AG - Plusbog.dk

Wireless Algorithms, Systems, and Applications - - Bog - Springer International Publishing AG - Plusbog.dk

An Introduction to the Planning Domain Definition Language - Patrik Haslum - Bog - Springer International Publishing AG - Plusbog.dk

An Introduction to the Planning Domain Definition Language - Patrik Haslum - Bog - Springer International Publishing AG - Plusbog.dk

Planning is the branch of Artificial Intelligence (AI) that seeks to automate reasoning about plans, most importantly the reasoning that goes into formulating a plan to achieve a given goal in a given situation. AI planning is model-based: a planning system takes as input a description (or model) of the initial situation, the actions available to change it, and the goal condition to output a plan composed of those actions that will accomplish the goal when executed from the initial situation. The Planning Domain Definition Language (PDDL) is a formal knowledge representation language designed to express planning models. Developed by the planning research community as a means of facilitating systems comparison, it has become a de-facto standard input language of many planning systems, although it is not the only modelling language for planning. Several variants of PDDL have emerged that capture planning problems of different natures and complexities, with a focus on deterministic problems. The purpose of this book is two-fold. First, we present a unified and current account of PDDL, covering the subsets of PDDL that express discrete, numeric, temporal, and hybrid planning. Second, we want to introduce readers to the art of modelling planning problems in this language, through educational examples that demonstrate how PDDL is used to model realistic planning problems. The book is intended for advanced students and researchers in AI who want to dive into the mechanics of AI planning, as well as those who want to be able to use AI planning systems without an in-depth explanation of the algorithms and implementation techniques they use.

DKK 519.00
1

Human Rights as Battlefields - - Bog - Springer International Publishing AG - Plusbog.dk

Concrete Abstractions - Wolfgang Schreiner - Bog - Springer International Publishing AG - Plusbog.dk

Scouting and Guiding in Britain - Catherine Bannister - Bog - Springer International Publishing AG - Plusbog.dk

Towards a Psychosomatic Conception of Hypochondria - Martine Derzelle - Bog - Springer International Publishing AG - Plusbog.dk

Towards a Psychosomatic Conception of Hypochondria - Martine Derzelle - Bog - Springer International Publishing AG - Plusbog.dk

Linear Fractional Transformations - Arseniy Sheydvasser - Bog - Springer International Publishing AG - Plusbog.dk

Insulting Music - Lily E. Hirsch - Bog - Springer International Publishing AG - Plusbog.dk

Doing Indefinite Time - Irene Marti - Bog - Springer International Publishing AG - Plusbog.dk

Discourses of Ageing and Gender - Clare Anderson - Bog - Springer International Publishing AG - Plusbog.dk

Mental Health: Intervention Skills for the Emergency Services - - Bog - Springer International Publishing AG - Plusbog.dk

Mental Health: Intervention Skills for the Emergency Services - - Bog - Springer International Publishing AG - Plusbog.dk

This book addresses the practical management of mental health scenarios in the emergency setting and offers first-hand reflections on how emergency nurses, practitioners and allied mental health professionals handle these situations. Responding to mental health needs in emergency situations can be profoundly complex. Frequently emergency nurses and other personnel express their feelings of powerlessness, as they do not know what to say or do in order to achieve the best outcome, and have concerns that their intervention may make the situation worse for those in their care. How a practitioner confronts the mental health encounter and takes the essential steps in managing the event can have a critical impact on how that person copes in the future. This book helps readers understand what is involved in mental health work in emergency situations, and the practical, psychosocial and spiritual tensions that arise from managing the event and the sequelae. Moreover, it shows that it may be possible to provide a more effective emergency mental health service. This unique edited book presents critical reflections on aspects of mental health work gathered from the ‘hands-on’ experiences of the personnel. Mental health encounters in the emergency context are described in detail, illustrating not only what emergency nurses and mental health workers ‘do’ when mental health crises occur, but also what they feel about what they ‘do’. Written by a diverse team of emergency and mental health nurses and allied professionals currently engaged in emergency care both in hospital and pre-hospital settings, this book will appeal to emergency nurses and allied health professionals alike.

DKK 426.00
1

Data Exploration Using Example-Based Methods - Matteo Lissandrini - Bog - Springer International Publishing AG - Plusbog.dk

Data Exploration Using Example-Based Methods - Matteo Lissandrini - Bog - Springer International Publishing AG - Plusbog.dk

Data usually comes in a plethora of formats and dimensions, rendering the exploration and information extraction processes challenging. Thus, being able to perform exploratory analyses in the data with the intent of having an immediate glimpse on some of the data properties is becoming crucial. Exploratory analyses should be simple enough to avoid complicate declarative languages (such as SQL) and mechanisms, and at the same time retain the flexibility and expressiveness of such languages. Recently, we have witnessed a rediscovery of the so-called example-based methods, in which the user, or the analyst, circumvents query languages by using examples as input. An example is a representative of the intended results, or in other words, an item from the result set. Example-based methods exploit inherent characteristics of the data to infer the results that the user has in mind, but may not able to (easily) express. They can be useful in cases where a user is looking for information in an unfamiliar dataset, when the task is particularly challenging like finding duplicate items, or simply when they are exploring the data. In this book, we present an excursus over the main methods for exploratory analysis, with a particular focus on example-based methods. We show how that different data types require different techniques, and present algorithms that are specifically designed for relational, textual, and graph data. The book presents also the challenges and the new frontiers of machine learning in online settings which recently attracted the attention of the database community. The lecture concludes with a vision for further research and applications in this area.

DKK 434.00
1

Scalable Processing of Spatial-Keyword Queries - Walid G. Aref - Bog - Springer International Publishing AG - Plusbog.dk

Scalable Processing of Spatial-Keyword Queries - Walid G. Aref - Bog - Springer International Publishing AG - Plusbog.dk

Text data that is associated with location data has become ubiquitous. A tweet is an example of this type of data, where the text in a tweet is associated with the location where the tweet has been issued. We use the term spatial-keyword data to refer to this type of data. Spatial-keyword data is being generated at massive scale. Almost all online transactions have an associated spatial trace. The spatial trace is derived from GPS coordinates, IP addresses, or cell-phone-tower locations. Hundreds of millions or even billions of spatial-keyword objects are being generated daily. Spatial-keyword data has numerous applications that require efficient processing and management of massive amounts of spatial-keyword data. This book starts by overviewing some important applications of spatial-keyword data, and demonstrates the scale at which spatial-keyword data is being generated. Then, it formalizes and classifies the various types of queries that execute over spatial-keyword data. Next, it discusses important and desirable properties of spatial-keyword query languages that are needed to express queries over spatial-keyword data. As will be illustrated, existing spatial-keyword query languages vary in the types of spatial-keyword queries that they can support. There are many systems that process spatial-keyword queries. Systems differ from each other in various aspects, e.g., whether the system is batch-oriented or stream-based, and whether the system is centralized or distributed. Moreover, spatial-keyword systems vary in the types of queries that they support. Finally, systems vary in the types of indexing techniques that they adopt. This book provides an overview of the main spatial-keyword data-management systems (SKDMSs), and classifies them according to their features. Moreover, the book describes the main approaches adopted when indexing spatial-keyword data in the centralized and distributed settings. Several case studies of {SKDMSs} are presented along with the applications and query types that these {SKDMSs} are targeted for and the indexing techniques they utilize for processing their queries. Optimizing the performance and the query processing of {SKDMSs} still has many research challenges and open problems. The book concludes with a discussion about several important and open research-problems in the domain of scalable spatial-keyword processing.

DKK 434.00
1

Semantic Relations Between Nominals, Second Edition - Diarmuid O Seagdha - Bog - Springer International Publishing AG - Plusbog.dk

Semantic Relations Between Nominals, Second Edition - Diarmuid O Seagdha - Bog - Springer International Publishing AG - Plusbog.dk

Opportunity and Curiosity find similar rocks on Mars. One can generally understand this statement if one knows that Opportunity and Curiosity are instances of the class of Mars rovers, and recognizes that, as signalled by the word on, rocks are located on Mars. Two mental operations contribute to understanding: recognize how entities/concepts mentioned in a text interact and recall already known facts (which often themselves consist of relations between entities/concepts). Concept interactions one identifies in the text can be added to the repository of known facts, and aid the processing of future texts. The amassed knowledge can assist many advanced language-processing tasks, including summarization, question answering and machine translation. Semantic relations are the connections we perceive between things which interact. The book explores two, now intertwined, threads in semantic relations: how they are expressed in texts and what role they play in knowledge repositories. A historical perspective takes us back more than 2000 years to their beginnings, and then to developments much closer to our time: various attempts at producing lists of semantic relations, necessary and sufficient to express the interaction between entities/concepts. A look at relations outside context, then in general texts, and then in texts in specialized domains, has gradually brought new insights, and led to essential adjustments in how the relations are seen. At the same time, datasets which encompass these phenomena have become available. They started small, then grew somewhat, then became truly large. The large resources are inevitably noisy because they are constructed automatically. The available corpora-to be analyzed, or used to gather relational evidence-have also grown, and some systems now operate at the Web scale. The learning of semantic relations has proceeded in parallel, in adherence to supervised, unsupervised or distantly supervised paradigms. Detailed analyses of annotated datasets in supervised learning have granted insights useful in developing unsupervised and distantly supervised methods. These in turn have contributed to the understanding of what relations are and how to find them, and that has led to methods scalable to Web-sized textual data. The size and redundancy of information in very large corpora, which at first seemed problematic, have been harnessed to improve the process of relation extraction/learning. The newest technology, deep learning, supplies innovative and surprising solutions to a variety of problems in relation learning. This book aims to paint a big picture and to offer interesting details.

DKK 604.00
1