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CS MSc Day March 8 Schedule!

2018-02-19

Three MSc theses to be presented on March 8, 2017.

Thursday March 8 is the day for coordinated master thesis presentations in Computer Science at Lund University, Faculty of Engineering. Four MSc theses will be presented.

The presentations will take place in the E-house, room E:2116. A preliminary schedule follows.

Note to potential opponents: Register as opponent to the presentation of your choice by sending an email to the examiner for that presentation (firstname.lastname@cs.lth.se). Do not forget to specify the presentation you register for! Note that the number of opponents may be limited (often to two), so you might be forced to choose another presentation if you register too late. Registrations are individual, just as the oppositions are! More instructions are found on this page.

 

E:2116

13:15

PRESENTEROskar Jermakowicz
TITLEScalable processing of globally crowd-sourced geolocation data
EXAMINERKrzysztof Kuchcinski
SUPERVISORSMarcus Klang (LTH), Rikard Windh (Combain Mobile AB)
ABSTRACT

Combain Mobile AB has an indoor positioning solution that is based on processing crowd-sourced geolocation data. While the incoming data is growing, Combain wants to investigate whether it is worth adapting their solution to a big data solution. In the master’s thesis a prototype is developed in Apache Spark that implements the core functionality of Combain’s indoor positioning solution. By deploying the prototype in the cloud on Amazon Web Services, tests were conducted and measurements were taken and compared to the current solution. This allowed a thorough evaluation considering aspects such as scalability, performance, cost efficiency and precision. The conclusion is that the current solution is sufficient today, but when the amount of users grows as predicted, a more scalable solution has to be considered. Results show that the prototype has several promising aspects, making it a viable foundation for a big data solution.

14:15

PRESENTERElin Blomstergren
TITLEExpanding the Concepts of Values and Costs
EXAMINERBjörn Regnell
SUPERVISORJohan Linåker (LTH)
ABSTRACT

With the changes that the rise of agile methodologies has brought, the practice of requirements prioritisation has become a central part of the development process. Agile requirements prioritisation focuses heavily on customer needs and implementation time, ignoring many other aspects that will affect the outcome of the software development. This master's thesis aims to identify a wider range of aspects that agile companies should discuss through a case study. The case company develops an open source product and has mostly market driven requirements engineering, resulting in many different opinions to take into account in the prioritisation process. The result from the case study is a proposed prioritisation model based on identified aspect with a discussion on how to apply the model in a company setting. The model describes value-adding aspects of product requirements with the themes Customers’ Needs, Product Quality, and Timeline. Cost-adding aspects are described with the themes Complexity and Implementation.

15:15

PRESENTERFiras Dib
TITLEA Multilingual Named Entity Recognition System based on Fixed Ordinally-Forgetting Encoding
EXAMINERJacek Malec
SUPERVISORPierre Nugues (LTH)
ABSTRACTThis thesis describes a system whose goal is to find named entities in text. The system uses an encoding method, called the fixed ordinally-forgetting encoding, to efficiently encode variable-length text. We applied this encoding to words and characters and we used the resulting vectors as features. The system is language agnostic, and has been evaluated and tested on multiple languages. The system uses annotated data, which is supplied by third parties, as the knowledge source. The system parses any given text and outputs a list of entities found in the text with the given entity class and position in the text. The system achieved an F1 score of 90.31 in the shared CoNLL2003 English task. In the TAC2017 competition, the system achieved a F1 score of 75.4 for English.

 

 

 



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