Taxonomies: Hidden but Critical Tools Marjorie M.K. Hlava President Access Innovations, Inc.

Industry in change Technology changes Evolving standards Mergers New buzzwords Hard to tell what is real

Popular Misconceptions Computers can do it all No need to index No need for thesauri or subject headings Full text gives all we need Automatic full text User friendly search engines Search engines are indexes User profiles provide the right context Data filters give right answers

Some of it is true What can we use? Automatic - semi - classification Depends….. Size of collection Cost of the effort

What’s in?? Taxonomies –thesauri –hierarchies - classification –categorization –browsing Wellformedness Bricks and mortar, i.e., profit

Options for Access/Control Keep track of the input –Thesaurus –Authority file Maximize the access –Search engine –Browse list Power of the word –McCain

What do we need? The basics... Authority file –People, places, things Taxonomy –Thesaurus* with authority file or document instance “Automatic” Classification

Thesaurus Construction Parts of a whole Noun and noun phrases People, places, things Actions and reactions Concepts and processes

Term Records - Thesaurus - format Main Entries Top Terms - TT Broader Terms - BT Narrower Terms - NT Scope Notes - SN History - HI Date Term - added/changed - DA

Thesaurus - Format Related Terms - RT See - S See Also - SA Use - U Use For - UF “Wellformedness” = W3C

What are the parts? Natural Language Processing Term forms Term Relationships Term Associations

Natural Language Processing Morphological Lexical Analysis Syntactic Numerical Phraseological Semantic Analysis Pragmatic

Seven Major Parts of NLP 1. Morphological – plural – past tense to present

Seven Major Parts of NLP 2. Lexical Analysis – part of speech tagging 3. Syntactic analysis – non phrase id –proper name boundary

Seven Major Parts of NLP 4. Numeric concept boundary 5. Semantic analysis –Proper name concept categorization –Numeric concept categorization –Semantic relation extraction 6. Phraseological - discourse analysis –Text structure identification

Seven Major Parts of NLP 7. Pragmatic analysis –Cause and effect relationships –Nurse and nursing –Common sense reasoning (buy  possess) –Who has x ? –These are the people who brought you.....

Say it another way Term standardization Term forms Term relationships Term associations Rule building / domain creation

Word Standardization Split out chemical & drug terms – Separates chemical & drug terms for special treatment Split out homonyms, non-English terms, and authority terms – Separates objects, proper names, place names, and dates for special treatment Run spelling standardization program – Identifies variant spellings

Word Standardization Run word standardization program – ie, ing, -ed, -s, es, pre-, non-, and “-” Match preferred terms and synonyms

Term Forms Noun Adjective Verb, adverb Singular, plural Initial articles Spelling variants

Term Forms Punctuation Capitalization Abbreviations

Term Relationships Generic Hierarchical Systematic Alphabetic Instance Poly-hierarchical

Term Associations Cross references All and some rule Associative terms Related terms

“Rule building”* process Put terms in context Group like categories Consider relationships Standardize variants Meld to a single concept rule How much is really automatic???

Domains Taxonomy Term Record - thesaurus Hierarchical Browse-able list Handout in Booth 150

What else can we have? Proximity Stemming (lemmatization) Truncation Statistical clustering Bayesian and others

Other terms and tools Neural networks Word normalization Lexical (word) networks Distance mapping Pattern recognition

Moving toward the search engines Term weighting Frequency counts Relevance Precision Recall

Classification of Evolving model… Noun Extractors Rule Based Systems Semantic Processors Fuzzy Search Systems Filtering Systems “Automatic Classification Systems”

(Semi) Automatic Indexing Basic theories Thesaurus construction Natural language processing Domain specific

Noun extractors Noun Extractors Use stop word list and frequency counts –Semio –Word Perfect 5.0 –Recon Prebuilt domains –Autonomy –Net Owl –Newsindexer

Rules Based Systems Rule Based –Data Harmony –API –DTIC –Mapit

Semantic Processors Synth Bank n-Stein - expected Quiver - beta

Fuzzy Search Systems Dr. Link Sovereign Hill

Filtering Systems Screaming Media Data Harmony

New Directions Topic Maps - TAO –Topic –Associations –Occurrences Relational Indexing Index Visualization Based on term records Add the search engines….

What’s a user to do? Enjoy the presentation What about a database producer? –Look the options, –Build from the basics –Evaluate the new tools –See it work before you buy

Give me your card I will the presentation tonight

Thank You Marjorie M.K. Hlava President, Access Innovations, Inc. Chairman, Data Harmony Booth 150