Nick Haddock - Information Retrieval and Text Mining Consultant

Text mining, sometimes alternately referred to as text data mining, roughly equivalent to text analytics, refers generally to the process of deriving high-quality information from text. High-quality information is typically derived through the dividing of patterns and trends through means such as statistical pattern learning. Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output. 'High quality' in text mining usually refers to some combination of relevance, novelty, and interestingness. Typical text mining tasks include text categorization, text clustering, concept/entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling (i.e., learning relations between named entities).

APPLICATIONS A growing number of applications use text analysis and language processing.	Contextual advertising Mobile services Social networking Legal e-discovery IT log file monitoring Customer comments and feedback Cloud storage services Compliance Enterprise search Extracting financial information E-commerce product and price extraction
TECHNIQUES Each application requires a blend of techniques. Which techniques work best for each application? And which modules or algorithms to use for each approach?	Search Natural language parsing and information extraction Text mining Text classification including sentence detection Text clustering Machine learning Part-of-speech tagging Semantic word-sense disambiguation Named-entity detection Keyword and phrase extraction Document relevance and relatedness
NEED A CONSULTANT?	A consultant can get you up to speed fast. Help you work out what to do and what not do -- avoid the pitfalls and blind alleys Quickly deploy best-of-breed algorithms
CONSULTING FOCUS Consulting can focus on one or more areas.	Training: Getting your team up to speed. Goals: Business goals, technical goals, user needs Feasibility: What is possible? Evaluation of algorithms: How to do it? Data experiments: Explore and test the approaches. Evaluation of components: Whether to build, re-use, or buy. Technology roadmap: How to roll out the solution. Recruitment: Finding the right staff. Implementation: Actually getting there.
SEARCH CONSULTING	Lucene search consulting