[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Deposits of clastic carbonate-dominated (calciclastic) sedimentary slope systems in the rock record have been identified mostly as linearly-consistent carbonate apron deposits, even though most ancient clastic carbonate slope deposits fit the submarine fan systems better. Calciclastic submarine fans are consequently rarely described and are poorly understood. Subsequently, very little is known especially in mud-dominated calciclastic submarine fan systems. Presented in this study are a sedimentological core and petrographic characterisation of samples from eleven boreholes from the Lower Carboniferous of Bowland Basin (Northwest England) that reveals a >250 m thick calciturbidite complex deposited in a calciclastic submarine fan setting. Seven facies are recognised from core and thin section characterisation and are grouped into three carbonate turbidite sequences. They include: 1) Calciturbidites, comprising mostly of highto low-density, wavy-laminated bioclast-rich facies; 2) low-density densite mudstones which are characterised by planar laminated and unlaminated muddominated facies; and 3) Calcidebrites which are muddy or hyper-concentrated debrisflow deposits occurring as poorly-sorted, chaotic, mud-supported floatstones. These

Phd by thesis

Data Mining Practical Machine Learning Tools and Techniques

http://mi.eng.cam.ac.uk/~sjy/papers/wiyo07.pdf

Partially observable Markov decision processes for spoken dialog systems

The potential for genome-wide association studies to relate phenotypes to specific genetic variation is greatly increased when data can be combined or compared across multiple studies. To facilitate replication and validation across studies, RTI International (Research Triangle Park, North Carolina) and the National Human Genome Research Institute (Bethesda, Maryland) are collaborating on the consensus measures for Phenotypes and eXposures (PhenX) project. The goal of PhenX is to identify 15 high-priority, well-established, and broadly applicable measures for each of 21 research domains. PhenX measures are selected by working groups of domain experts using a consensus process that includes input from the scientific community. The selected measures are then made freely available to the scientific community via the PhenX Toolkit. Thus, the PhenX Toolkit provides the research community with a core set of high-quality, well-established, low-burden measures intended for use in large-scale genomic studies. PhenX measures will have the most impact when included at the experimental design stage. The PhenX Toolkit also includes links to standards and resources in an effort to facilitate data harmonization to legacy data. Broad acceptance and use of PhenX measures will promote cross-study comparisons to increase statistical power for identifying and replicating variants associated with complex diseases and with gene-gene and gene-environment interactions.

/pdf/the-phenx-toolkit-get-the-most-from-your-measures-26t68ksl4o.pdf

The PhenX Toolkit: Get the Most From Your Measures

Horizon 2020 ICT Program Project SSIX: Social
Sentiment analysis financial IndeXes, has received
funding from the European Union’s Horizon 2020
Research and Innovation Program ICT 2014 - Information
and Communications Technologies under
grant agreement No. 645425

SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News

This paper presents a controlled language for ontology editing and a software implementation, based partly on standard NLP tools, for processing that language and manipulating an ontology. The input sentences are analysed deterministically and compositionally with respect to a given ontology, which the software consults in order to interpret the input's semantics; this allows the user to learn fewer syntactic structures since some of them can be used to refer to either classes or instances, for example. A repeated-measures, task-based evaluation has been carried out in comparison with a well-known ontology editor; our software received favourable results for basic tasks. The paper also discusses work in progress and future plans for developing this language and tool.

/pdf/clone-controlled-language-for-ontology-editing-37nd612ty6.pdf

CLOnE: controlled language for ontology editing

Mining social media for opinions is important to governments and businesses. Current approaches focus on sentiment and opinion detection. Yet, people also justify their views, giving arguments. Understanding arguments in social media would yield richer knowledge about the views of individuals and collectives. Extracting arguments from social media is difficult. Messages appear to lack indicators for argument, document structure, or inter-document relationships. In social media, lexical variety, alternative spellings, multiple languages, and alternative punctuation are common. Social media also encompasses numerous genres. These aspects can confound the extraction of well-formed knowledge bases of argument. We chart out the various aspects in order to isolate them for further analysis and processing.

/pdf/dimensions-of-argumentation-in-social-media-1y0at9kt7z.pdf

Dimensions of argumentation in social media

This collaborative report highlights the properties and prospects of Controlled Natural Languages (CNLs). The report poses a range of questions concerning the goals of the CNL, the design, the linguistic aspects, the relationships and evaluation of CNLs, and the application tools. In posing the questions, the report attempts to structure the field of CNLs and to encourage further systematic discussion by researchers and developers.

/pdf/on-controlled-natural-languages-properties-and-prospects-4adizcbys8.pdf

On controlled natural languages: properties and prospects

The growing maturity of Natural Language Processing (NLP) techniques and resources is dramatically changing the landscape of many application domains which are dependent on the analysis of unstructured data at scale. The finance domain, with its reliance on the interpretation of multiple unstructured and structured data sources and its demand for fast and comprehensive decision making is already emerging as a primary ground for the experimentation of NLP, Web Mining and Information Retrieval (IR) techniques for the automatic analysis of financial news and opinions online. This challenge focuses on advancing the state-of-the-art of aspect-based sentiment analysis and opinion-based Question Answering for the financial domain.

Brian Davis

Papers

SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News

CLOnE: controlled language for ontology editing

Dimensions of argumentation in social media

On controlled natural languages: properties and prospects

WWW'18 Open Challenge: Financial Opinion Mining and Question Answering