DNA-Based Indexing

2010 ◽  
Vol 2 (3) ◽  
pp. 25-45 ◽  
Author(s):  
Max H. Garzon ◽  
Kiran C. Bobba ◽  
Andrew Neel ◽  
Vinhthuy Phan
Keyword(s):  
Information Retrieval ◽  
Parallel Computing ◽  
Natural Language Processing ◽  
Language Processing ◽  
Self Assembly ◽  
Genomic Analysis ◽  
Massively Parallel ◽  
Text Data ◽  
Massively Parallel Computing ◽  
Potential Use

DNA has been acknowledged as a suitable medium for massively parallel computing and as a “smart” glue for self-assembly. In this paper, a third capability of DNA is described in detail as memory capable of encoding and processing large amounts of data so that information can be retrieved associatively based on content. The technique is based on a novel representation of data on DNA that can shed information on the way DNA-, RNA- and other biomolecules encode information, which may be potentially important in applications to fields like bioinformatics and genetics, and natural language processing. Analyses are also provided of the sensitivity, robustness, and bounds on the theoretical capacity of the memories. Finally, the potential use of the memories are illustrated with two applications, one in genomic analysis for identification and classification, another in information retrieval from text data in abiotic form.

Developing the Persian Wordnet of Verbs Using Supervised Learning

2021 ◽  
Vol 20 (4) ◽  
pp. 1-18
Author(s):  
Zahra Mousavi ◽  
Heshaam Faili
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Language Processing ◽  
Supervised Classification ◽  
Word Sense ◽  
Direct Influence ◽  
Training Set ◽  
Bilingual Dictionary ◽  
Automated Method ◽  
Princeton Wordnet

Nowadays, wordnets are extensively used as a major resource in natural language processing and information retrieval tasks. Therefore, the accuracy of wordnets has a direct influence on the performance of the involved applications. This paper presents a fully-automated method for extending a previously developed Persian wordnet to cover more comprehensive and accurate verbal entries. At first, by using a bilingual dictionary, some Persian verbs are linked to Princeton WordNet synsets. A feature set related to the semantic behavior of compound verbs as the majority of Persian verbs is proposed. This feature set is employed in a supervised classification system to select the proper links for inclusion in the wordnet. We also benefit from a pre-existing Persian wordnet, FarsNet, and a similarity-based method to produce a training set. This is the largest automatically developed Persian wordnet with more than 27,000 words, 28,000 PWN synsets and 67,000 word-sense pairs that substantially outperforms the previous Persian wordnet with about 16,000 words, 22,000 PWN synsets and 38,000 word-sense pairs.

Report on the 4th Joint Workshop on Bibliometric-Enhanced Information Retrieval and Natural Language Processing for Digital Libraries at SIGIR 2019

2019 ◽  
Vol 53 (2) ◽  
pp. 3-10
Author(s):  
Muthu Kumar Chandrasekaran ◽  
Philipp Mayr
Keyword(s):  
Information Retrieval ◽  
Natural Language Processing ◽  
Natural Language ◽  
Research And Development ◽  
Language Processing ◽  
Digital Libraries ◽  
State Of The Art ◽  
Shared Task ◽  
Processing Information ◽  
Joint Workshop

The 4 th joint BIRNDL workshop was held at the 42nd ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019) in Paris, France. BIRNDL 2019 intended to stimulate IR researchers and digital library professionals to elaborate on new approaches in natural language processing, information retrieval, scientometrics, and recommendation techniques that can advance the state-of-the-art in scholarly document understanding, analysis, and retrieval at scale. The workshop incorporated different paper sessions and the 5 th edition of the CL-SciSumm Shared Task.

scholarly journals How Language Shapes Prejudice Against Women: An Examination Across 45 World Languages

2020 ◽  
Author(s):  
David DeFranza ◽  
Himanshu Mishra ◽  
Arul Mishra
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Ongoing Debate ◽  
Text Data ◽  
Gender Prejudice ◽  
World Languages ◽  
The World ◽  
Present Context ◽  
The Common

Language provides an ever-present context for our cognitions and has the ability to shape them. Languages across the world can be gendered (language in which the form of noun, verb, or pronoun is presented as female or male) versus genderless. In an ongoing debate, one stream of research suggests that gendered languages are more likely to display gender prejudice than genderless languages. However, another stream of research suggests that language does not have the ability to shape gender prejudice. In this research, we contribute to the debate by using a Natural Language Processing (NLP) method which captures the meaning of a word from the context in which it occurs. Using text data from Wikipedia and the Common Crawl project (which contains text from billions of publicly facing websites) across 45 world languages, covering the majority of the world’s population, we test for gender prejudice in gendered and genderless languages. We find that gender prejudice occurs more in gendered rather than genderless languages. Moreover, we examine whether genderedness of language influences the stereotypic dimensions of warmth and competence utilizing the same NLP method.

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