What's new for Text in SAP HANA SPS 11

1© 2014 SAP AG or an SAP affiliate company. All rights reserved.
SAP HANA SPS 11 - What’s New?
Search, Text Analysis and Text Mining
SAP HANA Product Management December, 2015
(Delta from SPS 10 to SPS 11)

© 2015 SAP SE or an SAP affiliate company. All rights reserved. 3Public
Table
Search Models
In a search model you define the structure of your “search object”
and how it is exposed to an application
 Tables and joins
 Columns
– Defaults for search
– Weights for ranking
– Fuzziness
– Defaults for facets
Table
Model
Access

*any* View
search annotations
Search Models and Data Access
Table
Table
Model
Access
Table
Table
OData SQL
CDS View
w/ search annotations
Table
Table
OData SQL
*any* View
search annotations
JSON JSON JSON
CALL ESH_CONFIG(configuration)
Built-in procedure to add search annotations
(request/response, facets, UI areas etc.) to views
CALL ESH_SEARCH(query,?)
Built-in procedure to search on multiple search
models with an “OData” query and a “JSON”
response
Fiori
SAP HANA SPS10 SAP HANA SPS11

ESH_CONFIG and ESH_SEARCH
SAP HANA SPS11 supports adding “search annotations” to existing views.
Search annotations are added in a CDS-like format, using the built-in procedure ESH_CONFIG.
ESH_SEARCH is the new search API
• Federated search across multiple search models in a single call
• Based on OData v4, response is JSON
• Search specific extensions, e.g. Search.score(), Search.search()

Search Model Example
CALL ESH_CONFIG('[{
"uri": "~/$metadata/EntitySets", "method": "PUT",
"content":{
"Fullname": "DMM264/V_DOCUMENTS",
"EntityType": {
"@Search.searchable": true,
"@EnterpriseSearch.enabled": true,
"Properties": [
{"Name": "ID", "@Search.defaultSearchElement": true, "@EnterpriseSearch.key": true, "@EnterpriseSearch.presentationMode": [ "TITLE" ]},
{"Name": "AUTHOR", "@EnterpriseSearch.usageMode": [ "AUTO_FACET" ],"@EnterpriseSearch.presentationMode": [ "SUMMARY" ]},
{"Name": "CATEGORY", "@EnterpriseSearch.usageMode": [ "AUTO_FACET" ],"@EnterpriseSearch.presentationMode": [ "SUMMARY" ]},
{"Name": "TITLE", "@Search.defaultSearchElement": true, "@EnterpriseSearch.highlighted.enabled": true, "@Search.ranking":
"HIGH","@EnterpriseSearch.presentationMode": [ "TITLE" ]},
{"Name": "CONTENT", "@Search.defaultSearchElement": true, "@EnterpriseSearch.snippets.enabled": true,
@Search.fuzzinessThreshold": 0.9, "@Search.ranking": "MEDIUM","@EnterpriseSearch.presentationMode": [ "DETAIL" ]}
]
}
}
}]
',?);
existing view
expose as facet
search in this column relevance ranking

Data Access Example
CALL ESH_SEARCH('[
"/$all?facets=all&$filter=Search.search(
query=''scope:V_DOCUMENTS merkel'')&$top=10"
]', ?);

Search Response Example
1st result item
2nd result item
1st facet

How to find SAP HANA documentation on this topic?
SAP HANA Advanced Data Processing
 What’s New in the SAP HANA Advanced Data
Processing (Release Notes)
 Development
– File Loader Guide for SAP HANA
– SAP HANA Search Developer Guide
 References
– SAP HANA INA Search JavaScript
• In addition to this learning material, you can find SAP HANA documentation on the
SAP Help Portal knowledge center at http://help.sap.com/hana_options_adp.
• The knowledge center is structured according to the product lifecycle: installation, security, administration,
development.

Agenda – Text Analysis
New or Improved Features
 Grammatical Role Analysis
 Text Analysis XS API – Document Metadata
 Dictionaries – Case Sensitivity
 Language Column – SAP Language Codes
 Tolerant Stemming: Dutch, English, German, Italian
 Linguistic Analysis: Hungarian and Romanian
 Core Extraction: Korean
 Voice of Customer: English and German

New Grammatical Role Analysis (1/2)
Optional analyzer for English that identifies syntactic relationships between elements of a sentence in
the form of subject–verb–object expressions, commonly known as ‘triples’.
The [SUBJECT]big brown cat[/SUBJECT] on the red couch was [VERB]eating[/VERB] a
[DIRECTOBJECT]dead mouse[/DIRECTOBJECT].
The following grammatical roles describe arguments of verbs that are supported:
• Subject person, place, thing, or idea that is doing or being something: Oracle bought Responsys.
• DirectObject recipient of the action: Oracle bought Responsys.
• IndirectObject affected by the action but not primary object: Oracle offered Responsys an improved contract.
• OtherObject often prepositional object: They talked about the contract.
• Predicate object of the verb to be: This is a revised version.
An additional grammatical role supported, which does not describe a function with respect to a verb:
• PredicateSubject subject of a predicative expression: The contract is new.

New Grammatical Role Analysis (2/2)
Input:
Oracle was rumored to buy marketing-software maker Responsys Inc. for $1.5 billion.
Output:
TA_RULE TA_COUNTER TA_TOKEN TA_TYPE TA_PARENT TA_OFFSET
Entity Extraction 1 Oracle ORGANIZATION/COMMERCIAL ? 0
Entity Extraction 2 marketing-software maker NOUN_GROUP ? 26
Entity Extraction 3 Responsys Inc. ORGANIZATION/COMMERCIAL ? 51
Entity Extraction 4 $1.5 billion CURRENCY ? 70
Grammatical Role 5 Oracle Subject 7 0
Grammatical Role 6 Oracle Subject 8 0
Grammatical Role 7 rumored Root/MainVerb/Passive ? 11
Grammatical Role 8 buy MainVerb/Active ? 22
Grammatical Role 9 marketing-software maker Responsys Inc. DirectObject 8 26
Grammatical Role 10 $1.5 billion OtherObject/for 8 70
Notes:
• Core extraction is included in the configuration (1 - 4)
• Each grammatical role is either the governor (verb) or dependent (verb argument)
• TA_TYPE holds the details about its grammatical role
• TA_PARENT holds the TA_COUNTER value of its corresponding governor
• It is possible for a single dependent to be the argument (5 and 6) of two different verbs

Improved Text Analysis XS API – Document Metadata
For on-demand processing, text analysis output can be accessed via the SAP HANA Extended
Application Services (XS) API:
• Alternative to persisting output data to the $TA table
• Bypasses creating the full-text index
Now the following metadata properties for documents can be optionally included:
• Author
• Date
• Date Created
• Date Modified
• Description
• Keyword
• Language
• Subject
• Title
• Version
• FromEmailAddress
• FromName
• ToEmailAddress
• ToName
• CcEmailAddress
• CcName
• BccEmailAddress
• BccName

Improved Dictionaries – Case Sensitivity
In the context of extraction,
dictionaries are user-defined
repositories of entities.
Dictionaries are used for customized information about the
entities your application must find.
Dictionaries can be used to store name variations in a structured
way that is accessible through the extraction process.
Dictionary XML syntax now includes the option:
<dictionary xmlns=“http://www.sap.com/ta/4.0” case-sensitive=“true”>
: :
</dictionary>
For example, adding the attribute will ensure the dictionary entry
WHO will match WHO and not who or Who.
The default behavior is case-insensitive.

Improved Language Column – SAP Language Codes
You can specify the input language for each row.
Use LANGUAGE COLUMN to bypass automatic language detection:
 Specify ISO 639 language code or…
 SAP language codes can now be optionally utilized
 English = E, French = F, German = D, etc.
This option allows configuring full-text search over existing SAP business applications without
modifying the underlying database tables.
CREATE FULLTEXT INDEX PRODUCT_REVIEWS_IDX ON PRODUCT_REVIEWS(CONTENT) FAST PREPROCESS OFF
LANGUAGE COLUMN LANGUAGE;

Improved Stemming – Dutch, English, German, Italian
Stemming identifies the base form referenced in a dictionary.
Tolerant stemming is introduced for Dutch, English, German and Italian. This default behavior allows
for handling non-standard spellings to better maximize recall.
For example in English, the stemmer handles spelling variation found in American and British English;
does not require correct capitalization and accentuation and allows required hyphens to be optional.

Improved Language Support for Hungarian and Romanian
Full linguistic analysis support by adding Part-of-
Speech (POS) tagging and Noun Group (concept)
extraction for Hungarian and Romanian.
Language
LINGANALYSIS_BASIC
LINGANALYSIS_STEMS
LINGANALYSIS_FULL
Arabic  
Catalan  
Chinese (Simplified)  
Chinese (Traditional)  
Croatian  
Czech  
Danish  
Dutch  
English  
Farsi  
French  
German  
Greek 
Hebrew  
Hungarian   NEW
Indonesian  
Italian  
Japanese  
Korean  
Norwegian (Bokmal)  
Norwegian (Nynorsk)  
Polish  
Portuguese  
Romanian   NEW
Russian  
Serbian  
Slovak  
Slovenian  
Spanish  
Swedish  
Thai  
Turkish  

TITLE President
PERSON Barak Obama
LOCALITY Cambridge
REGION@MINOR Napa County
REGION@MAJOR Connecticut
COUNTRY Brazil
CONTINENT South America
GEO_FEATURE Mount Fuji
GEO_AREA Scandinavia
FACILITY Logan International Airport
LOCALITY New Delhi
ORGANIZATION@COMMERCIAL AT&T
ORGANIZATION@EDUCATIONAL University of Washington
ORGANIZATION@OTHER FBI
SOCIAL_MEDIA@TWITTER_ID @SAP
SOCIAL_MEDIA@TWITTER_TOPIC #HANA
DATE 2/14/2011
DAY Monday
MONTH June
YEAR 2011
PHONE 617-677-2030
URI@EMAIL john.smith@sap.com
URI@URL http://sap.com
Improved Core Extraction for Korean
Higher precision and recall on existing predefined core extractions.

Improved Voice of Customer – English and German
Set of rules to extract sentiments expressed about a product or a service:
I [love] [my new phone]!  Strong positive sentiment about my new phone
He did [not like] [the book].  Weak negative sentiment about the book
More granular than competing systems because it can link sentiments with topics:
[love my new phone] = Sentiment
‘love’ = StrongPositiveSentiment
‘my new phone’ = Topic
Determiners (above strikethroughs) are now not included with the topic classifications for English and German.
This is a change to the previous behavior as it simplifies topic aggregation.

 Development
– SAP HANA Text Analysis Developer Guide
 References
– SAP HANA Text Analysis Extraction Customization Guide
– SAP HANA Text Analysis Language Reference Guide
– SAP HANA Text Analysis XS JavaScript API
development.

Agenda – Text Mining
New or Improved Features
 Language Support
 Automatic Stop Words

Text Mining Recap
Text mining provides statistical functions that
can compare documents by examining the
terms used within them.
The term-document matrix (a.k.a. text mining
index) is an optional data structure that is
optimized through the results of text
analysis.
Text mining is bound to the full-text indexing
and text analysis process.
Full-textindex
Text
analysis
results
table
Full-text
indexing
with TA
and TM
Term-document
matrix
TM config.
Insert
ID TITLE

New Language Support
Text mining is now natively integrated with all 32 languages supported by text analysis.
It leverages the available text preprocessing steps:
 Tokenization
 Stemming
 Part-of-Speech tagging

Improved Stop Word Customization
Stop words are lists of literal terms to ignore in order to focus
on the important content.
Text mining automatically filters terms to include only nouns
based on their part-of-speech tags for 31 languages.
Optionally, users can manually include additional stop words
in the configuration properties.
Language Automatic Stop Words
Arabic 
Catalan 
Chinese (Simplified) 
Chinese (Traditional) 
Croatian 
Czech 
Danish 
Dutch 
English 
Farsi 
French 
German 
Greek
Hebrew 
Hungarian 
Indonesian 
Italian 
Japanese 
Korean 
Norwegian (Bokmal) 
Norwegian (Nynorsk) 
Polish 
Portuguese 
Romanian 
Russian 
Serbian 
Slovak 
Slovenian 
Spanish 
Swedish 
Thai 
Turkish 

 Development
– SAP HANA Text Mining Developer Guide
 References
– SAP HANA Text Mining XS JavaScript API
– SQL Reference for Options
development.

Disclaimer
This presentation outlines our general product direction and should not be relied on in making
a purchase decision. This presentation is not subject to your license agreement or any other
agreement with SAP.
SAP has no obligation to pursue any course of business outlined in this presentation or to
develop or release any functionality mentioned in this presentation. This presentation and
SAP’s strategy and possible future developments are subject to change and may be changed
by SAP at any time for any reason without notice.
This document is provided without a warranty of any kind, either express or implied, including
but not limited to, the implied warranties of merchantability, fitness for a particular purpose, or
non-infringement. SAP assumes no responsibility for errors or omissions in this document,
except if such damages were caused by SAP intentionally or grossly negligent.

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