Editor for this issue: Naomi Ogasawara <naomi
linguistlist.org>
Rank of Job: Areas Required: Computational Linguist Other Desired Areas: any programming ability University or Organization: COREintellect Department: State or Province: Texas Country: USA Final Date of Application: n/a Contact: Michael Seeley mseeleyMail to author|Respond to list|Read more issues|LINGUIST home page|Top of issuecoreintellect.com Address for Applications: 13765 Beta Road Dallas TX 75244 USA Description of Work Duties: To assist in the development of NL-related tools and architectures for the COREintellect product range. NL tasks will be as varied as document segmentation, efficient spelling-correction algorithms, syntactic parsing of NL questions and the construction of semantic representations thereof, phrase extraction from free text, recognition of novel named entities, lexicon construction (and the leveraging of public domain components such as WordNet) and sentence generation (expressing answers to NL questions in a readable form). Required Skills (Mandatory): Bsc/BA in Computer Science, Mathematics, Engineering A linguistics degree with extensive course-work on computational topics is equally relevant. Practical programming experience with Java, C++ or C, particularly in the domain of efficient parser construction. Preferred Skills (Desirable): Msc/MA or PhD in Computer Science, Artificial Intelligence, Computational Linguistics or a related discipline. Experience with Finite State approaches to language modeling. Object-Oriented design experience/skills. Lex and Yacc experience. Lexicon construction skills, in particular the utilization of third-party components such as WordNet. Useful Interview Questions: What do you consider to be the limitations of a Finite-State approach to language modeling? What benefits does such an approach offer? What is the problem with left recursion? Does it afflict both top-down and bottom-up approaches? How easy would it be to implement a generic chart-parsing class in Java? What benefits, if any, can be had by integrating WordNet into a language model. What are its limitations?