Innovative, knowledgeable computational linguist with over 10 years' experience. Strong background in both theoretical linguistics and computer science with specific knowledge of several Middle Eastern and AfPak languages. Experience in Machine Translation, Entity Extraction, Social Media analysis, and other areas of Natural Language Processing.
Low-density languages raise difficulties for standard approaches to natural language processing t... more Low-density languages raise difficulties for standard approaches to natural language processing that depend on large online corpora. Using Persian as a case study, we propose a novel method for bootstrapping MT capability for a low-density language in the case where it relates to a higher density variant. Tajiki Persian is a low-density language that uses the Cyrillic alphabet, while Iranian
We have developed a rich markup language called SpatialML for spatial locations, allowing potenti... more We have developed a rich markup language called SpatialML for spatial locations, allowing potentially better integration of text collections with resources such as databases that provide spatial information about a domain, including gazetteers, physical feature databases, mapping services, etc. ... Our focus is primarily on geography and culturally-relevant landmarks, rather than biology, cosmology, geology, or other regions of the domain of spatial language. However, we expect that these guidelines could be adapted to other such domains with ...
Low-density languages raise difficulties for standard approaches to natural language processing t... more Low-density languages raise difficulties for standard approaches to natural language processing that depend on large online corpora. Using Persian as a case study, we propose a novel method for bootstrapping MT capability for a low-density language in the case where it relates to a higher density variant. Tajiki Persian is a low-density language that uses the Cyrillic alphabet, while Iranian
We have developed a rich markup language called SpatialML for spatial locations, allowing potenti... more We have developed a rich markup language called SpatialML for spatial locations, allowing potentially better integration of text collections with resources such as databases that provide spatial information about a domain, including gazetteers, physical feature databases, mapping services, etc. ... Our focus is primarily on geography and culturally-relevant landmarks, rather than biology, cosmology, geology, or other regions of the domain of spatial language. However, we expect that these guidelines could be adapted to other such domains with ...
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Papers by Dan Parvaz