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Master Thesis purpose: Improved collaboration and shared understanding between organizations using NLP and semantic technology
We want to explore the possibilities to use Topic Modeling, Formal Concept Analysis, Natural Language Processing, semantic technologies, and Business Rules to facilitate a cheap, fast, and systematic approach to create and maintain a common (internal) language for our Business Support System portfolio (BSS-O, an Ericsson BSS ontology). In the first phase, we want to focus on the dialogue between R&D and Service Delivery organizations related to automatic testing. The ambition is to make a proof-of-concept including an evaluation with proposed next steps.
1th Use Case:
Create, maintain and improve a BSS-O (e.g., using supervised learning and strict governance). With such a BSS-O, the basic features would be to get early detection/warning of potential quality aspects derived from an interaction between two actors (in their roles). Examples of indicators are level of uncertainty, risk level for misunderstanding, level of (new) complexity, level of correctness, level of completeness (…let us identify more essential measurements as part of the task).
2nd Use Case:
To analyze and compare a new text (e.g., customer contract, test specification, requirement) to the BSS-O baseline (is there a difference comparing two texts?). What would be the recommended steps towards an augmented text editing environment?
3rd Use Case:
Compare a specialized (smaller) ontology towards the overall BSS-O. Examples of specialized ontologies are the 5G standard, the BSS Customer Product Information etc. What indicators would be useful for this analysis? Is a different learning strategy needed for a specialized vs a broad ontology?
Generally, we are looking at reducing the time and effort needed for time-consuming but simpler tasks, e.g.
Improving the definition of automatic test cases
Building UC automatically as a complement to the standard agreement
Maybe 75% of the requirements (RFx/SoC) can be managed by a machine
Early detection of requirement misunderstanding between 2 roles (e.g., MA vs. Customer, MA vs. Solution Architects, Solution Architect vs. System Architect)
Applications of the technology
A typical application would be for Pre-sales to scan a customer’s Request For Information (RFI) to detect early risks in a customer dialogue, and help sales navigate and steer the customer in the customer dialogue and contract negotiation. In this way, Ericsson should always translate all customer dialogues (based on customer’s language) into an internal BSS-O based understanding of the customer’s needs so that Ericsson can leverage our broad customer base.
Another more advanced example of application is to create a systematic approach for how to work with a customer contract in the early phases of a sales opportunity. Modify an existing standard contract, and by generating a skeleton of test cases for how to validate the customer contract, the terms and wordings (identified by our tool above) can be used to define the needed contractual Business Flexibility (as an exercise of writing Business rules to enhance the test skeleton). By putting Business Flexibility with these business rules (and test skeletons) under strict governance, we can systematically improve our standardized customer contract skeletons, as well as create a foundation for automatic acceptance tests.
If you feel interested, please send in your application as soon as possible. The start date can be adjusted to both your and the business needs – the intention is to start in November 2019.
While applying please attach your updated CV, current grades and cover letter written in English into one document (under CV field in the application tool) and clearly define your technical knowledge.
If you have any additional questions, please contact our Recruiter Elzbieta Penpeska at email@example.com
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Primary country and city: Sweden (SE) || || Karlskrona || Stud&YP
Req ID: 302978