kms web interface_eng
TRANSCRIPT
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INTRODUCTIONKey concept about Big Data Analysis
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KMS: from Information Overload to Knowledge Mining
The number of available documents has grown exponentially during past years, while our reading and analysis skill has remained unchanged during time.
Research Engines reply to our query with long lists of documents, whose pertincence, relevance and utility is often unclear.
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KMS: from Information Overload to Knowledge Mining
How to create value from this chance of data access?
How to turn it into useful and efficient knowledge for a company?
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KMS: from Information Overload to Knowledge Mining
The idea is to consider this extended set of texts and documents (Big Data) like a mine to explore aiming at finding interesting information and discovering potential connections, both unexpected and hidden at a first glance.
Knowledge Mining is the answer to Information Overload, for information and data management.
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The Knowledge Mining System (KMS) platform captures informations through a crawling system capable of analyzing term or concept recurrences.It splits analyzed texts by relevance and significance and it identifies connections and relationships between concepts and topics,and finally files all the categorized data for future consultations.
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KMS: from Information Overload to Knowledge Mining
This Analysis Methodology is based on automatic analysis technologies typical of Natural Language, and it’s organized in two steps:■ Semantic/Linguistic Analysis, which analyze the key linguistic elements of every word
(grammar category, inflection and conjugation features)■ Statistic Analysis which appoints to elaborated and “conceptualized” documents,
tematic topicset predefined and customized through the association between themes and topics.
Inside a text, it’s not simply the existence of keywords that makes it relevant, but it’s the contextualization that allows us to extract useful informations, in order to find the answers we’re looking for.
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KMSDefinition and Access Information
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KMS is a web tool that allows research, consultation and analysis of potential informations of interest, acquired through the crawling of online sources.
Service Adress:
kms.synuosa.com
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KMS: USERS DASHBOARD
Once you have logged into the system with your users, it is possible to explore and read informations filed through different functionalities and the related analysis functions.
In particular it is possible to make both qualitative and quantitative analysis, evaluating different depth levels and informations connections.
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KMS: DASHBOARD UTENTE
Interface Version
Functionalities for data analysis
User Informations
General informations,research archives
Setting Informations
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FUNCTIONALITIESFeatures description and how-to-use
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QUANTITATIVE ANALYSIS
Through the Quantitative Analysis functionality it is possible to display: ■ quantitative global enhancement, distributed by source, source’s type, and general
sentiment for the most influential sources. ■ macro view of trends and relative overall numericals■ chance of setting research filters and display details informations.
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Number of information extracted with the search
Sources distribution by domain name
Search Time Period
Domain Source and number of related mentions
QUANTITATIVE ANALYSIS
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Sources Type■ newspaper■ forum■ blog■ community■ social network■ encyclopedia■ institutional
Grouping according to sources type, based on
content and information characteristics
QUANTITATIVE ANALYSIS
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Sentiment distribution, related to mentions analyzed by source
Overall Sentiment of Sources
Domain Sources and number of related mentions
QUANTITATIVE ANALYSIS
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Sentiment’s buzz evaluated by related mentions
Number of analyzed mentions distibuted by
month / day / hour / minute
QUANTITATIVE ANALYSIS
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Filter setting dashboard, related to informations
displayed on graphs
QUANTITATIVE ANALYSIS
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Reading area and quick reference of selected
mentions
[ ! ] NOTESWhith only a click on graphs, it’s possible to display information detailes through the read area of selected mentions
QUANTITATIVE ANALYSIS
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SEMANTIC SEARCH
Through the General Search functionality it is possible to realize and save researches with keywords on the whole documents repository.
Data extraction allows the display of relevant mentions with sentiment evaluation, the concept cloud of those most frequently connected to the research and a rappresentation of quantitive data divided by source, source’s type, sentiment and buzz.
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SEMANTIC SEARCH
Textual Reasearch display,by natural language
Search Time Period
Concepts Selection
Information Search Mode regarding target concepts
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SEMANTIC SEARCH
Extended view of mentions content
Mentions sentiment value
Mentions Extra information
Reading area of extracted mentions
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Informations Display normalized through a
concept cloud
Cloud Filters and SettingsDisplay
Informazioni aggiuntive relative alla mention
Concept Cloud’s display area
[ ! ] NOTEthe Cloud allows to make a new research simply by clicking on a concept; the system creates a new cloud on the selected concept.
SEMANTIC SEARCH
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SEMANTIC SEARCH
Quantitative data display area
[ ! ] NOTETypes of information and functionalities are the same of QUANTITATIVE ANALYSIS
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DIFFERENZA TRA TAG CLOUD E CONCEPT CLOUD KMS
“Standard” Tag Cloud, generated by terms recurrence. Recurrence means the number of time the single word is counted in order to generate the visual weight and the size.
KMS Concept Cloud generated through concepts normalization and significancy, linked to research topics. Through a process of connections analysis between contents in relation to research topics, it establish the value and weight of the individual concept compared to others.
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QUALITATIVE ANALYSIS
Through the Qualitative Analysis functionality, the system allows the collection and the accurate information analysis, searchable by a streamlined interrogation language, the natural language.
Besides the quantitative informations, the funcionality allows to analyze documents through: ■ a map of concepts linked to the search’s keyword in the form of concept cloud■ a navigation map through concepts, based on logical-functional connections between
them (WHO DOES WHAT, WHERE, WHEN, HOW)
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QUALITATIVE ANALYSIS
Textual Reasearch display,by natural language
Search Time Period
Concepts Selection
Information Search Mode regarding target concepts
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QUALITATIVE ANALYSIS
Quantitative DataDisplay Area
[ ! ] NOTETypes of information and functionalities are the same of QUANTITATIVE ANALYSIS
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QUALITATIVE ANALYSIS
[ ! ] NOTETypes of information and functionalities are the same of GENERAL RESEARCH
Reading area of extracted mentions
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QUALITATIVE ANALYSIS
[ ! ] NOTETypes of information and functionalities are the same of GENERAL RESEARCH
Concept Cloud Display Area
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QUALITATIVE ANALYSIS
Navigation Map Display Area
The connections between concepts are displayed with conjuction lines.Thickness and Direction depends on information’s flow and quantity
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USE OF THE NAVIGATION MAP
By examining connections, it is possible to highligths the more significant logic relations between concepts.
For Example this case higlights:
Trio Living > passeggino(stroller) >> stretto (tight)With a simple click it is possible to display connection details and read the information
“for my experience the stroller is too tight, and it’s impossible to use it.”
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USE OF THE NAVIGATION MAP
Further example of relevant connection:
costringere (force) > a cambiare (to change) > passeggino (stroller)
“the stroller’s sitting is the tightesmade by Chicco, so when the your baby will grow up, you’ll have to change stroller.”
“How to end this unpleased adventure: I spent 600€ during October 2009, and on march 2010 I have to change stroller....”
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CONTEXT ANALYSIS
Through the Context Analysis functionality it is possible to detect the sentiment rate for each product category or topic of interest, and to analyze the connections between concepts and topics, based on their level of criticality .
The functionality, in addition of detecting the polarity, by recording the users’ tone, detects and differentiates his opinion in relation to differents features of the product/service (overall satisfaction, quality/prize value, safety, design, etc)
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CONTEXT ANALYSIS
Thus it is possible to have an immediate and accurate picture of critics and/or positive areas, by highlithing who and where is talking about it.
This gave the chance to plan targeted answers or operations in order to solve difficult situations, and/or leverage the positive assets and the motivations which obtain most acceptance.
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CONTEXT ANALYSIS
Setting area of alert system Number of entities of
interest defined by the system
Search period definition
selection of key concept of interest
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CONTEXT ANALYSIS
KMS rate: monitoring global index based on the mention’s polarity, related
to the target concept
Number of evidences detected inside the mentions related to the target concept
Reading area and general classification of
informations related to target concepts
Quick creation of alert monitoring
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CONTEXT ANALYSIS
Polarity value distributionbased on evidences
Evaluation and distribution of quantitative and
sentiment values about mentions
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CONTEXT ANALYSIS
Quick reading area of selected mentions
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CONTEXT ANALYSIS
Comparison area of target concepts
Sentiment buzz evaluated on detectedmentions that are
related totarget concepts
Mention buzz detected by minute during the selected
monitoring period
Target concepts list, detected during the selected monitoring period
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MONITORING SETTINGS
Through the Monitoring Setting functionality it’s possible to set up an alert system, based on previously programmed events .
The functionality allows to:■ select concepts, connections and topics upon which the alert can be set.■ set up the comments positivity/negativity limits, above wich you want to be warned by
email or RSS feed.■ schedule alert’s sending time, according to company’s needs
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MONITORING SETTINGS
Alert systemconfiguration area
quick activation/deactivationof alert set up
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MONITORING SETTINGS
parameters of configuration
Selection of topics and concepts to monitor
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MONITORING SETTINGS
Quick reading areaof evidences extracted by
the alert system selection of evidences detected and filed
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LIVE ANALYSIS
Through the live analysis funcionality it is possible to monitor in real time the users activity flow on the main social networks.
The Live Analysis allows to understand the appreciation in real time of a show, and to analyze what people think and how they judge it.
In particular it is possible to know in real time how users interact on Twitter and Facebook during, i.e., a tv or radio show, by evaluating quantitative and qualitative features, related to target concepts and topics of interest.
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LIVE ANALYSIS
The concepts cloud of live analysis creates an automatic association of concepts and expressions sentiment, useful to easly highlights the elements that define the success or the failure of an event.
It’s a first glance to understand what’s working well and what isn’t, to seize upon both positive and negative features
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LIVE ANALYSIS
live analysis systemconfiguration area
configuration of update frequency and monitoring period
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LIVE ANALYSIS
Detected mention and avarage per minuteduring the selected
monitoring period
Update frequencycontroll timer
Active users and avarege per minute during the selected monitoring period
Max number of mentions detected minute by minute and moment
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LIVE ANALYSIS
Sentiment buzz, evaluated on mentions detected
minute by minute during the selected monitoring period
Topic sentiment distribution, on mentions detected during the selected monitoring period
Viewing area of informations detected in
real time
Mentions trend detected minute by minute during the
selected monitoring period
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LIVE ANALYSIS
Selection of target concepts of interest for the monitoring
target concepts comparison area, detected
in real time
Mentions trend, detected related to selected target
concepts
Sentiment buzz, evaluated on mentions detected
related to selected target concepts
Target concepts list, detected during the selected monitoring period
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LIVE ANALYSIS
most recurrent positive and negative tags related to
target concept
Number of detected evidences in the whole
mentions related to target concept
polarity value distribution on evidences related to target concept
KMS rate: global monitoring index, defined
on evidence polarity and mentions sentiment,
related to target concept
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KMS MOBILE APPCharacteristics and Features
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The access to KMS platform includes the chance of using the new mobile app, available for iOS and Android.
The use of the smartphone app allows the access to the Quantitative Analysis, the Semantic Search and Monitoring Setting functionalities.
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KMS MOBILE APP
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