50 ways to make   computers  understandnatural language
with 6 keytechniques
Classifiers  Bayesian ClassifiersSupport Vector Machine
Sentence Parsing   & Tagging      Treat gem   Ruby Linguistics     Open Calais     Achemy API
Dictionaries  Ruby WordNet Create your own
Pattern MatchingRegular Expressions (also great for          normalising)
Meta DataHTML, headers, microformats,    author information
Statistical   AnalysisKeyword density, worddistribution, word/time       distribution
1Person NamesSemantic Tagging/Dictionary
2 Location NamesSemantic Tagging + Geocode with    Yahoo API/Google Maps
3Important Words  Dictionary, Meta Data
4  Email Address           Pattern matching/b[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,4}b/
5Phone Numbers           Pattern matching/b[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,4}b/
6Postal Address        Pattern matchingdetect postal code or town/city and work backwards
7Dates & TimesDictionary, Pattern matching,        Chronic Gem
8Company/Org Semantic Tagging
9   Natural PhenomenonSemantic Tagging, Dictionary
10Job Title Dictionary
11     TopicClassifier/Dictionary
12       QuotesPattern Matching & Semantic          Tagging
13CurrencyPattern Matching
14Language Classifier
15    SentimentClassifier/Dictionary/Pattern         Matching
16Potty Mouth/DHH Detector F-bomb dictionary
17FlamboyanceDictionary or Classifier
18 AgeClassifier
19         WealthDictionary/Classifier/Meta data
20HumourDictionary
21       Gender or Dictionary (first names)Classifier (guess from writing            style)
22Author Location    Meta Data
23 Person DetailsMeta Data: Wikipedia, Rapleaf
24Keyword Density   Frequency analysis
25    Relationship        GraphsMeta    Semantic Tagging,   Data(Showing connectionsbetween people mentioning each        ...
26      Clusteringk-means clustering, hierarchical, clustering, density clustering,             rsruby
27    Influencial      PeopleSemantic Tagging, Statistical         Analysis
28Influential LinksPattern Matching, Statistical         Analysis
29Social Graph   Meta Data
30Link ThumbnailsPattern Matching, Meta data
31Link Media TypePattern Matching, Meta Data or          Dictionary
32Domain DetailsMeta Data (whois, alexa, ip,        geocode)
33   Active TimeMeta Data, Statistical Analysis
34      Generosity(Through citation e.g. RT) Pattern    Match, Semantic Tagging
35      Similarity  Statistical Analysis: cosinesimilarity, vector space model
36Ethnicity Classifier
37Expertise Levelinfluence + topic + dictionary
38Tech Savviness previous or Classifier
39 DeviceOwnershipMeta data, dictionary
40Favourite BrandsSemantic Tagging or Dictionary + Sentiment Analysis + Frequency            Analysis
41    Favourite Shopping timesSemantic Tagging or Dictionary + Sentiment Analysis + Frequency            Analysis
42Favourite websitePattern matching + SentimentAnalysis + Frequency Analysis
43Organisation or    Person Meta data or classifier
44 Happiest PlacesMeta data, geocoding, sentiment,       statistical analysis
45 Happiest TimesMeta data, sentiment, statistical            analysis
46Personality Type     Classifier
47Humanality  Classifier
48Spam Detection    Classifier
49Product/Brand/  Film league        dictionary,sentiment analysis, statistical          analysis
50 FormalityClassifier/Dictionary
?
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50 Ways to Makes Sense Of Natural Language

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  • 50 Ways to Makes Sense Of Natural Language

    1. 1. 50 ways to make computers understandnatural language
    2. 2. with 6 keytechniques
    3. 3. Classifiers Bayesian ClassifiersSupport Vector Machine
    4. 4. Sentence Parsing & Tagging Treat gem Ruby Linguistics Open Calais Achemy API
    5. 5. Dictionaries Ruby WordNet Create your own
    6. 6. Pattern MatchingRegular Expressions (also great for normalising)
    7. 7. Meta DataHTML, headers, microformats, author information
    8. 8. Statistical AnalysisKeyword density, worddistribution, word/time distribution
    9. 9. 1Person NamesSemantic Tagging/Dictionary
    10. 10. 2 Location NamesSemantic Tagging + Geocode with Yahoo API/Google Maps
    11. 11. 3Important Words Dictionary, Meta Data
    12. 12. 4 Email Address Pattern matching/b[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,4}b/
    13. 13. 5Phone Numbers Pattern matching/b[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+.[a-zA-Z]{2,4}b/
    14. 14. 6Postal Address Pattern matchingdetect postal code or town/city and work backwards
    15. 15. 7Dates & TimesDictionary, Pattern matching, Chronic Gem
    16. 16. 8Company/Org Semantic Tagging
    17. 17. 9 Natural PhenomenonSemantic Tagging, Dictionary
    18. 18. 10Job Title Dictionary
    19. 19. 11 TopicClassifier/Dictionary
    20. 20. 12 QuotesPattern Matching & Semantic Tagging
    21. 21. 13CurrencyPattern Matching
    22. 22. 14Language Classifier
    23. 23. 15 SentimentClassifier/Dictionary/Pattern Matching
    24. 24. 16Potty Mouth/DHH Detector F-bomb dictionary
    25. 25. 17FlamboyanceDictionary or Classifier
    26. 26. 18 AgeClassifier
    27. 27. 19 WealthDictionary/Classifier/Meta data
    28. 28. 20HumourDictionary
    29. 29. 21 Gender or Dictionary (first names)Classifier (guess from writing style)
    30. 30. 22Author Location Meta Data
    31. 31. 23 Person DetailsMeta Data: Wikipedia, Rapleaf
    32. 32. 24Keyword Density Frequency analysis
    33. 33. 25 Relationship GraphsMeta Semantic Tagging, Data(Showing connectionsbetween people mentioning each other)
    34. 34. 26 Clusteringk-means clustering, hierarchical, clustering, density clustering, rsruby
    35. 35. 27 Influencial PeopleSemantic Tagging, Statistical Analysis
    36. 36. 28Influential LinksPattern Matching, Statistical Analysis
    37. 37. 29Social Graph Meta Data
    38. 38. 30Link ThumbnailsPattern Matching, Meta data
    39. 39. 31Link Media TypePattern Matching, Meta Data or Dictionary
    40. 40. 32Domain DetailsMeta Data (whois, alexa, ip, geocode)
    41. 41. 33 Active TimeMeta Data, Statistical Analysis
    42. 42. 34 Generosity(Through citation e.g. RT) Pattern Match, Semantic Tagging
    43. 43. 35 Similarity Statistical Analysis: cosinesimilarity, vector space model
    44. 44. 36Ethnicity Classifier
    45. 45. 37Expertise Levelinfluence + topic + dictionary
    46. 46. 38Tech Savviness previous or Classifier
    47. 47. 39 DeviceOwnershipMeta data, dictionary
    48. 48. 40Favourite BrandsSemantic Tagging or Dictionary + Sentiment Analysis + Frequency Analysis
    49. 49. 41 Favourite Shopping timesSemantic Tagging or Dictionary + Sentiment Analysis + Frequency Analysis
    50. 50. 42Favourite websitePattern matching + SentimentAnalysis + Frequency Analysis
    51. 51. 43Organisation or Person Meta data or classifier
    52. 52. 44 Happiest PlacesMeta data, geocoding, sentiment, statistical analysis
    53. 53. 45 Happiest TimesMeta data, sentiment, statistical analysis
    54. 54. 46Personality Type Classifier
    55. 55. 47Humanality Classifier
    56. 56. 48Spam Detection Classifier
    57. 57. 49Product/Brand/ Film league dictionary,sentiment analysis, statistical analysis
    58. 58. 50 FormalityClassifier/Dictionary
    59. 59. ?
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