HAMBURG KOPENHAGEN LAUSANNE MÃNCHEN STUTTGART WIEN ZÃRICH. NLG - Natural Language Generation ..... Trivadis triCast. T
NLG - Natural Language Generation Enter Narratives Trivadis triCast 29.05.2018, 16:00 bis 17:00 Uhr Isabela Anciutti Stefan Bartram
@trivadis
BASEL BERN BRUGG DÜSSELDORF HAMBURG KOPENHAGEN LAUSANNE
tricast
FRANKFURT A.M. FREIBURG I.BR. GENF MÜNCHEN STUTTGART WIEN ZÜRICH
Speaker Isabela Anciutti Consultant
[email protected]
Stefan Bartram Senior Partner Manager
[email protected]
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11.06.2018
Trivadis triCast
Trivadis triCast Format Tuesday at 4 p.m.
Talk, questions and answers
Current IT topics, Trivadis point of view webcast will be recorded
Short surveys Option for questions via question menu
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11.06.2018
Trivadis triCast
Training with quality & success guarantee
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11.06.2018
https://www.trivadis.com/en/training Trivadis triCast https://www.trivadis.com/en/training
NLG - Natural Language Generation
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11.06.2018
Trivadis triCast
NLG – Natural Language Generation Enter Narratives
Isabela Anciutti
BASEL BERN BRUGG DÜSSELDORF HAMBURG COPENHAGEN LAUSANNE
FRANKFURT A.M. FREIBURG I.BR. GENEVA MUNICH STUTTGART VIENNA ZURICH
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NLG - Natural Language Generation
AGENDA 1. Introduction 2. Trivadis POC
3. Narratives
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NLG - Natural Language Generation
Introduction
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NLG - Natural Language Generation
Definition NLG, Narratives or aka Data Story-Telling: Data in, Language out! “It’s like a translator that converts a computer-based representation into a natural language representation”
Computational Linguistics + Language-oriented Artificial Intelligence Expertise in: – Linguistics – Psychology – Engineering – Computer Science 10
NLG - Natural Language Generation
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NLG - Natural Language Generation
Advantages
Conclusion – Speeds the data understanding, reduces manual analysis, accelerates decisionmaking and makes insights more accessible
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NLG - Natural Language Generation
NLG Package What do you need to pack for NLG? – An NLG Engine – Data Sets – Generation Grammar
For example, using Template Method: – Raw data – Definition of labels – Definition of KPIs
– Thresholds 13
NLG - Natural Language Generation
Trivadis POC
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NLG - Natural Language Generation
CV as first exposure to customer Consultant’s Business Card – Our customer receives Resumes per e-mail – New applications at customers every month
Winning impression • Professional, updated, straight to business • Better first impression of company and of employee • Wins in a comparison with other candidates’ Resumes
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NLG - Natural Language Generation
Paid alternative Writing or rewriting of summary by consultants • Expected little compliance or no significant improvement • Consultants missing Resume in a given language • New consultants start from scratch • Final text still needs review
Cost of writing and/or reviewing the Resume Summaries by an agency • 450+ CVs: 1 hour/CV • Recurrent cost based on continuous hiring and career progress
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NLG - Natural Language Generation
Target format Summary made of 4-5 statements containing • Relevant experience • Unique skills/qualities • Highlights/accomplishments • Languages What a Resume’s summary should avoid • Simple repetition of Resume’s contents • List of values, like IT tools or job roles • Chronological descriptions: since then, after that, beginning in 2005, etc. • Direct references implying gender and names (these shouldn’t be relevant) 17
NLG - Natural Language Generation
CV Data – Valued and categorized variables Variable course_teach_cnt exp_year_cnt industry_cnt language_cnt last_role_title last_role_years_cnt presentation_publication_cnt project_cnt role_cnt skill_cnt skill_expert_cnt skill_guru_cnt technology_cnt
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Value 2 23 8 4 Senior Consultant 13 10 69 7 184 48 2 29
Category CAT_RSH_1 CAT_EXP_3 CAT_IND_2 CAT_LNG_3 CAT_EXP_2 CAT_RSH_3 CAT_PRO_3 CAT_ROL_2 CAT_SKL_3 CAT_SKL_3 CAT_SKL_3 CAT_TEK_3
NLG - Natural Language Generation
Variable Value course_teach_cnt 4 exp_year_cnt 16 industry_cnt 8 language_cnt 3 last_role_title Principal Consultant last_role_years_cnt 3 presentation_publication_cnt 24 project_cnt 139 role_cnt 7 skill_cnt 105 skill_expert_cnt 34 skill_guru_cnt 4 technology_cnt 38
Category CAT_RSH_2 CAT_EXP_3 CAT_IND_2 CAT_LNG_3 CAT_EXP_1 CAT_RSH_3 CAT_PRO_3 CAT_ROL_2 CAT_SKL_2 CAT_SKL_3 CAT_SKL_3 CAT_TEK_3
Results Target descriptive CV: – “Accomplished retail manager with more than five years of extensive retail, sales & hospitality background. First sales consultant to reach 5,000 clients for XYZ agency with generated sales of over $500,000. Quality writing and communication skills, multilingual (Spanish/Portuguese/German) and a strong passion for the hospitality/hotel industry.”
Resulting descriptive CV: – “Dynamic Senior Consultant applying know-how and leading business for more than two decades. Determined guru with miscellaneous publications and while effectively producing a multifold of vibrant projects. Enthusiastic and communicative. Efficiently engaging no less than 29 different technologies, specially succeeding at plenty of industry sectors and an authority in many roles.” – “Communicative Principal Consultant contributing on strong enterprises for close to twenty years. With many optimal skills and specially excelling in a lot of sectors. Self-confident and ambitious. Responsibly mastering more than 38 distinct applications, handling plenty of roles and with more than 139 projects.”
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NLG - Natural Language Generation
Narratives
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NLG - Natural Language Generation
NLG Engines:
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NLG - Natural Language Generation
NLG Engines:
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NLG - Natural Language Generation
Partners
NLG Engines:
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NLG - Natural Language Generation
Examples
NLG Engines:
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NLG - Natural Language Generation
Partners
NLG Engines:
Example Tableau Narratives for Tableau™ is an extension for Google Chrome that automatically generates insightful stories about visualizations created in Tableau Server 10.0, Tableau Public, and Tableau Online.
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NLG - Natural Language Generation
NLG Engines:
Example Qlik Sense® Qlik Sense® analytics software is a business intelligence tool designed for the enterprise. Narratives for Qlik is an extension for Qlik Sense.
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NLG - Natural Language Generation
NLG Engines: Power BI
Example Microsoft Narratives for Power BI enables Power BI users to immediately gain insight from all of their data by transforming it into intelligent narratives.
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NLG - Natural Language Generation
NLG Engines: Lumira
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NLG - Natural Language Generation
Example SAP BO
By 2019, natural-language generation will be a standard feature of 90% of modern BI and analytics platforms.
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NLG - Natural Language Generation
Q&A Tel. +41 79 909 7217
[email protected]
BASEL BERN BRUGG DÜSSELDORF HAMBURG COPENHAGEN LAUSANNE
FRANKFURT A.M. FREIBURG I.BR. GENEVA MUNICH STUTTGART VIENNA ZURICH
Output Results Turnover ($ thousand) Mobile Car Cosmetics Food Travel
Jan
Feb
Mar
Apr
May
Jun
120
125
130
121
111
160
212
250
165
150
160
120
56
76
60
65
29
18
345
467
289
565
530
480
2065
0
0
0
0
4533
Turnover report for the month of June The total turnover for all divisions was $5.3 Million. There was an extreme rise (640%) in relation to the previous gain on the month before (92%). 31
NLG - Natural Language Generation
Output Results Turnover in thousand $ Mobile Car Cosmetics Food Travel
Jan
Feb
Mar
Apr
May
Jun
120
125
130
121
111
160
212
250
165
150
160
120
56
76
60
65
29
18
345
467
289
565
530
480
2065
0
0
0
0
4533
Turnover report for the month of June In two divisions only, the turnover increased during the month of June compared to the previous months (Travel and Mobile). 32
NLG - Natural Language Generation
Output Results Turnover in thousand $ Mobile Car Cosmetics Food Travel
Jan
Feb
Mar
Apr
May
Jun
120
125
130
121
111
160
212
250
165
150
160
120
56
76
60
65
29
18
345
467
289
565
530
480
2065
0
0
0
0
4533
Turnover report for the month of June Caveat: The Cosmetics division needs closer surveillance: in June the turnover for Cosmetics fell below the minimum turnover goal set. 33
NLG - Natural Language Generation
POC targets Targets ✓
Creation of support tables: verbs, adjectives and terms
• 180 adjectives, 46 pronouns, 41 adverbs, 109 verbs ✓
Categorization of subject’s skills for the proper use of adjectives
• For each topic a category and a level from 1-3 ✓
Calculation of topic’s weight based on the individual content
• Estimation can be optimized ✓
Randomization of synonyms usage
• 71 statement templates
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Results (cont.) Resulting templates: • Adjective job title Experience. Accomplishment. Accomplishment. Adjective and adjective. Accomplishment, Accomplishment and Accomplishment.
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NLG - Natural Language Generation
SQL Server
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NLG - Natural Language Generation
BI Challenges (cont.) Translation of data into sentences • 23 years of experience, 69 projects, 7 different roles: with more than 20 years of success projects occupying roles
Wide range of vocabulary to maintain diversity across pool ✓ Text templates using statement templates using term’s lists
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NLG - Natural Language Generation
Wordsmith and Alexa
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NLG - Natural Language Generation
NLG Techniques Canned Text ▪ Simplest ▪ Single and Multi Phrase ▪ Trivial to create
▪ Very inflexible
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Template
Phrase-based
▪ Pre-defined templates
▪ Generalized templates
▪ Unique set of features
▪ Flexible alterations
▪ Recursive phrasal patterns at different levels
▪ Each possible expression alternative
▪ Multisentence ▪ For regular texts
NLG - Natural Language Generation
▪ Complex
Feature-based
▪ Singlesentence
Fragen und Antworten Isabela Anciutti Consultant
[email protected]
Stefan Bartram Senior Partner Manager
[email protected]
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11.06.2018
Trivadis triCast
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11.06.2018
Trivadis triCast
Thanks for joining! Stefan Bartram Senior Partner Manager Tel. +49 89 99 27 59 322
[email protected]
@trivadis
tricast