Enhancing pencil drawing patterns via using semantic information

Author(s):  
Teng Li ◽  
Jianyu Xie ◽  
Hongliang Niu ◽  
Shijie Hao
2012 ◽  
Author(s):  
Darya L. Zabelina ◽  
Emmanuel Guzman-Martinez ◽  
Laura Ortega ◽  
Marcia Grabowecky ◽  
Mark Beeman ◽  
...  

2010 ◽  
Vol 3 (1) ◽  
pp. 1-30 ◽  
Author(s):  
Heike Baeskow

For many decades there has been a consensus among linguists of various schools that derivational suffixes function not only to determine the word-class of the complex expressions they form, but also convey semantic information. The aspect of suffix-inherent meaning is ignored by representatives of a relatively new theoretical direction – Neo-Construction Grammar – who consider derivational suffixes to be either purely functional elements of the grammar or meaningless phonological realizations of abstract grammatical morphemes. The latter view is maintained by adherents of Distributed Morphology, who at the same time emphasize the importance of conceptual knowledge for derivational processes without attempting to define this aspect. The purpose of this study is first of all to provide support for the long-standing assumption that suffixes are inherently meaningful. The focus of interest is on the suffixes -ship, -dom and -hood. Data from Old English and Modern English (including neologisms) will show that these suffixes have developed rich arrays of meaning which cannot be structurally derived. Moreover, since conceptual knowledge is indeed an important factor for word-formation processes, a concrete, theory-independent model for the representation of the synchronically observable meaning components associated with -ship, -dom and -hood will be proposed.


1982 ◽  
Author(s):  
Ralph Grishman ◽  
Lynette Hirschman ◽  
Carol Friedman

2019 ◽  
Vol 23 (1) ◽  
pp. 377-384
Author(s):  
Naren J ◽  
Raja Rajeswari D ◽  
Nikhith Sannidhi ◽  
Vithya G

Author(s):  
Sheng Zhang ◽  
Qi Luo ◽  
Yukun Feng ◽  
Ke Ding ◽  
Daniela Gifu ◽  
...  

Background: As a known key phrase extraction algorithm, TextRank is an analogue of PageRank algorithm, which relied heavily on the statistics of term frequency in the manner of co-occurrence analysis. Objective: The frequency-based characteristic made it a neck-bottle for performance enhancement, and various improved TextRank algorithms were proposed in the recent years. Most of improvements incorporated semantic information into key phrase extraction algorithm and achieved improvement. Method: In this research, taking both syntactic and semantic information into consideration, we integrated syntactic tree algorithm and word embedding and put forward an algorithm of Word Embedding and Syntactic Information Algorithm (WESIA), which improved the accuracy of the TextRank algorithm. Results: By applying our method on a self-made test set and a public test set, the result implied that the proposed unsupervised key phrase extraction algorithm outperformed the other algorithms to some extent.


Author(s):  
Christopher McCarroll

This chapter draws together the different strands of the book and it also resolves some outstanding issues, responding to some questions that were left unanswered. If autobiographical memory can involve memories of repeated or more generic events, can the field and observer perspective distinction be usefully applied in these cases? If autobiographical memory becomes semanticized over time, do observer perspectives involve more semantic information? What does remembering from-the-outside tell us about the nature of personal memory and the ways we have of getting outside of ourselves? This chapter answers questions such as these and summarizes the progress made by the book on understanding the nature of personal memory and the perspectival mind.


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