213,264 research outputs found
The topic-prominence parameter
No full textThis article aims to recast the properties of topic-prominent languages and their differences from subject-prominent languages as documented in the functionalist literature into the framework of the Principle-and-Parameter approach. It provides a configurational definition of the topic construction called Topic Phrase (TP), with the topic marker as its head. The availablity of TP enables topic prominent languages to develop various topic structures with properties such as morphological marking; cross-categorial realization of topics and comments; and mutiple application of topicalization. The article elaborates the notion of topic prominence. A topic prominent language is characterized as one that tends to activate the TP and to make full use of the configuration. Typically, it has a larger number and variety of highly grammaticalized topic markers in the Lexicon and permits a variety of syntactic categories to occur in the specifier position and the complement position of TP
topicmodels: An R Package for Fitting Topic Models
No full textTopic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent variables which are referred to as topics. The R package topicmodels provides basic infrastructure for fitting topic models based on data structures from the text mining package tm. The package includes interfaces to two algorithms for fitting topic models: the variational expectation-maximization algorithm provided by David M. Blei and co-authors and an algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors.
topicmodels: An R Package for Fitting Topic Models
No full textTopic models allow the probabilistic modeling of term frequency occurrences in documents.
The fitted model can be used to estimate the similarity between documents as
well as between a set of specified keywords using an additional layer of latent variables
which are referred to as topics. The R package topicmodels provides basic infrastructure
for fitting topic models based on data structures from the text mining package tm. The
package includes interfaces to two algorithms for fitting topic models: the variational
expectation-maximization algorithm provided by David M. Blei and co-authors and an
algorithm using Gibbs sampling by Xuan-Hieu Phan and co-authors
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
Functional similarities between bimanual coordination and topic/comment structure
No full textHuman manual action exhibits a differential use of a non-dominant (typically, left) and a dominant (typically, right) hand. Human communication exhibits a pervasive structuring of utterances into topic and comment. I will point out striking similarities between the coordination of hands in bimanual actions, and the structuring of utterances in topics and comments. I will also show how principles of bimanual coordination influence the expression of topic/comment structure in sign languages and in gestures accompanying spoken language, and suggest that bimanual coordination might have been a preadaptation of the development of information structure in human communication
NOx Emissions Control Area (NECA) scenario for ports in the North Adriatic Sea
No full textIn response to global warming, the International Maritime Organisation (IMO) set rules of 50% Greenhouse Gas (GHG) reduction by 2050, from 2008 levels. Signatory countries to the IMO's regulation require frequent assessment of the contribution of GHG emissions from shipping calling at their ports or trading in their territorial waters to ensure their compliance with the regulations. This demands a rapid and accurate method to assess shipping's contribution to GHG emissions. Current methodologies for estimating emissions from ships can be described on a scale between bottom-up and top-down methods. Top-down methods provide rapid estimates – primarily based on fuel sales reports - without considering individual vessel details. Therefore, they are less accurate and do not provide a breakdown of emissions by ship types or in specific regions. Bottom-up methodologies are detailed vessel-based estimates; however, they are data and time-demanding. The Ship Emissions Assessment method (SEA) (Topic et al., 2021) fills the gap between bottom-up and top-down methods by providing an innovative hybrid solution for rapid but accurate ship emission estimation. It uses publicly available, cost-effective data sets for emission estimates. The SEA method is capable of estimating ships' emissions in designated areas to understand regulations' effectiveness and provide emission quantification evidence. This research objective was to apply the SEA method to quantify CO2, SOX and NOX exhaust emissions from containerships for the three crucial containership ports: Trieste, Rijeka and Venice, in the North of the Adriatic Sea. The SEA methodology was applied to assess emissions and forecast efficiency in scenarios of different regulatory measures. A reduction in NOx emissions was estimated for the event of the implementation of NECA in all three ports. Results showed that 447.13 tonnes of NOx could be reduced each year in the North Adriatic Sea area around the ports of Rijeka, Trieste and Venice in the event that NECA regulations are stipulated.</p
Topic structures and minimal effort
No full textThe complexity of human languages has always inspired research for some human faculty that makes language learning possible. The system that generates the complexity of human languages, ideally, is simple and effective. Recent developments of the generative grammatical theory explore deeper into the issue of simplicity or economy. The Minimalist Program developed in Chomsky (1991, 1993, 1995) tries to provide contents to such notions. What does it mean to be more economic or least effort? An important instantiation of such notions is the proposal that movement is the last resort assuming that movement is more costly than non-movement. Processes occur only because they are necessary. The definition of necessity generally is cast in morphological terms. Moreover, the notion of "economy" or "least effort" is deterministic of the appropriate derivations for sentences: a shorter derivation is better than a longer one. In this work, we show that the notion of "least effort," - do minimally if possible - is manifested not only in derivations but also in other aspects of the grammar. We take Chinese as an example and show that this language exhibits the properties manifesting some "least effort" guidelines in the area of movement and reconstruction, and in the projection of syntactic positions: when there is a choice, non-application of moyement/reconstruction and non-projection of a position are adopted. These phenomena essentially are attested in topic structures. The question arises as to why topic structures exhibit such minimal effort effects. We suggest that this is due to the fact that topic structures can be derived by movement or base-generation. When there are morpho-syntactic clues that reconstruction is necessary, the structure is a movement structure. Otherwise, the less costly non-movement structure is assumed. Moreover, because of the possibility of assuming a topic NP to be base-generated, bearing a predication (or aboutness) relation with the comment clause, the argument position which otherwise would be related to the topic (conveniently termed the trace position) is not projected when there is a choice of projecting or not projecting it
Navigating through archives, libraries and museums: Topic Maps as a harmonizing instrument
No full textThe paper deals with the possibility of creating a topic map based system where different sectors of cultural heritage would interact with users, by monitoring the navigation histories of users and the statistics on the searches, in order to authorize variant form of names. The problem of managing different sectors and harmonizing them both from a structural and a semantic view point, by using Topic Maps, is also discussed. With regards to this, we are introducing two projects, which are largely based on the above mention use of Topic Maps.
The original publication is available at www.springerlink.com http://www.springerlink.com/content/6k5473124678k452/fulltext.pd
Concept Extraction and Clustering for Topic Digital Library Construction
No full textThis paper is to introduce a new approach to build
topic digital library using concept extraction and
document clustering. Firstly, documents in a special
domain are automatically produced by document
classification approach. Then, the keywords of each
document are extracted using the machine learning
approach. The keywords are used to cluster the
documents subset. The clustered result is the taxonomy
of the subset. Lastly, the taxonomy is modified to the
hierarchical structure for user navigation by manual
adjustments. The topic digital library is constructed
after combining the full-text retrieval and hierarchical
navigation function
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