Import from database or file
Import open text from a database field or from file folders with possible OCR of scanned documents.
THE SEMANTICS TO INCREASE DATA ANALYSIS CAPABILITY AND IMPROVE STRATEGIC DECISIONS
The instrument SemantiCase
SemantiCase is a simple but powerful software procedure for analyze all types of open texts through NLP models, reducing effort and complexity of the analysis. Semanticase integrates models of Natural Language Processing and Understanding, machine learning, statistics and IT.
By integrating into its back-end of complexes mathematical-probabilistic models of semantic representation, allows each operator to start the analysis through a user-friendly system, delegating the intervention of the subject matter expert, not in the onerous phase of data classification and organization, but directly in the most crucial phase of interpreting the results. Through the dashboard, a representation of the data is available facilitating the analysis of qualitative phenomena and the reporting to support decision-making processes.
The semantic analysis of texts, in fact, makes it possible to integrate the usual decision-making processes, making usable and enhancing qualitative information that is generally difficult to grasp, if not through an expensive processing.
The open text, in addition to specific contents, is also characterized by connotations on attitudes, experiences and personal opinions. The text immediacy and complexity offers the writer a broader perimeter of expression and allows for an authentic communication of meanings. Being able to grasp all the texts senses and specificities through comparison and synthesis methods is the mission of Semanticase.
Semanticase for HR - Human Resources
Semantic analysis is applied in the HR field in the various phases of Human Resource management, bringing to light the meanings expressed in open texts and making a contribution to knowledge to assume efficient decision-making behaviors.
Some application examples:
Semanticase for digital learning
It's possible to use Semanticase for various uses in the digital learning field.
Some examples are:
Semanticase for Customer Care
Semantic analysis can be used in the context of customer assistance for the systematic study of the flow of commercial and technical complaints sent away by customers and / or requests for assistance (also including voice messages). It is possible to analyze the complaint topics, the trends over time, the sentiment index and investigate the predictive words of churn / termination.
Semanticase for document management
Application of semantic analysis techniques for the analysis of corporate documentation, also in order to integrate semantics into document management processes.
An example of application: compliance of documents
Application of semantic analysis techniques aimed at checking the compliance of the security risk assessment documentation (defined on a regulatory and internal regulation level).
The compliance analysis is conducted by measuring the degree of adequacy / semantic proximity for each risk area through the expression of a probabilistic score with respect to the defined system of rules. This indication can be integrated into document analysis prioritization processes.
Import open text from a database field or from file folders with possible OCR of scanned documents.
Import open text and voice from one or more groups, broadcast lists or whatsapp numbers.
Import open text from audio files and voice messages via
speech-to-text.
speech-to-text.
Identify the most popular words by frequency and rank them according to the different states of a variable.
Identify the distinctive and exclusive words for each state of a structured variable that accompanies the texts
Analyze the polarization of opinions, their trend over time and in relation to covariates; emotions’ analysis.
Identify transversal themes in texts through the construction of stochastic models of the co-occurrences of words
Studying the characteristic words of a theme in relation to the state of the covariates associated to the text.
Studying issues based on descriptive co-variations using both linear and mixed-effect models
Writing is always hiding something,
so that it is later discovered
Italo Calvino - If a Traveler on a Winter's Night (1979)
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SINGLE LICENSE
Data Analysis Service
Basic configuration: SI
Type of report:
based on the volume of data
Data processing:
based on the processing data volumei
Specialist consultancy for the interpretation of the results:
based on the number of reports
DEVELOPER LICENSE
Software license
Setup: SI
Type of report:
based on the data volume
Data processing:
based on the processing data volumei
Training: SI
Operator License: 1
Viewing License: 5
Basic fee Months:
duration of your choice (from the month, on a quarterly, half-yearly or annual basis)
Upon request, integration of the results with:
WEBSEM month
Monthly chatbot
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