Wednesday, July 23, 2008

What's your favorite language?

Huh? Seriously?
You mean, programming languages are not just tools?
I say, show me the project and I'll tell you which language I prefer for it.
You won't call in a French interpreter to translate an English-Corean dialog, will you. In a similar fashion, specific programming tasks almost require specific type of programming tools. The right language for the job may not be your favorite but then this only means that this programming job is not your favorite thing to do either. Also a French interpreter could possibly re-train and learn to do Korean interpretations. He will still be using a language to do his job and the basic methodology will remain the same; only the language "rules" will have changed. Similarly, regardless of what your current programming expertise is, what counts is that you are familiar with and eventually applying the same intrinsic methologies and principles of programming. So, what's really a "favorite language"?

Tuesday, July 22, 2008

Text Analytics Java development (job post)

Text Analytics Developer - Java - Computational Linguistics
in US-IL-Chicago

Company: CyberCoders Engineering
Location: Chicago, IL

What you need to apply:

# A strong background in Computational Linguistics or Natural Language Processing.
# Proven ability to deliver text mining or information retrieval solutions for real world applications
# Demonstrates and applies thorough understanding of software development methodology and protocols.
# Excellent programming skills in Java
# Expert-level understanding of machine learning and statistical techniques as applied to text analytics, e.g., information extraction, summarization, classification, clustering, tone/sentiment analysis, relevance ranking
# Experience in the creation and exploitation of domain and task ontologies in text analytics are a plus
# A background check will be required; holding an active security clearance is a plus.

What you will be doing:

# Developing and implementing commercial software applications.
# Identifying and modifying existing algorithms, code implementation, testing, and maintenance.
# Development will be done in the Java programming language and will integrate with the D2K analytics development environment unless specified otherwise.
# Work within the Analytics Group in planning and executing the creation and delivery of text analytic features.

What's in it for you:

# An attractive compensation plan including cash, stock and bonus is available to the right candidate.

Required Skills
Text Analytics Developer, Java, Computational Linguistics, Natural Language Processing, Text Analytics, Information Extraction, Summarization, Classification, Clustering, Tone Analysis, Sentiment Analysis, Relevance Ranking, D2K

Relevant background includes:
Text Analytics Developer, Java, Computational Linguistics, Natural Language Processing, Text Analytics, Information Extraction, Summarization, Classification, Clustering, Tone Analysis, Sentiment Analysis, Relevance Ranking, D2K

The following job types are relevant:
Information Technology, Engineering, Professional Services

How to apply:
Through the company's website.
Recruiter's Name: Reggie Landicho
Job ID: RL-TextAnalyticsDev-IL6

Friday, July 18, 2008

Diigo

A new way to keep track of information you find on the web and share it with friends. Also a new way to connect with people all over the world who share your bookmarks and therefore interests. Visit Diigo and start marking up and sharing the web with your like-minded buddies. Learn more about the Nevada-based start-up at: About Diigo.

Wednesday, July 16, 2008

start-up effort in sentiment detection and analysis

"Semantic analysis" or "semantic measurement" or "sentiment detection" are very popular with startup's. Take for instance ScoutLabs and SkyGrid. The former capitalizes on the early warning detection of security-related events in news and the latter is watching negative and positive sentiment in news about business in order to inform stock market trends. In both occasions, the sentiment analysis technology relies heavily on automatically analyzing natural language input in unstructured form and filling records of a database with the extracted/tagged information. One has to wonder about the limitations of database systems for successfully undertaking such task.