Theses

Now showing 1 - 3 of 3

Embargo
Enhancing the value proposition of priority Banking in SriLanaka
(Sri Lanka Institute of Information Technology, 2025-10) NAWARATHNE,I.K.S.S.
Priority banking has become a vital strategic focus for banks and financial institutions aiming to retain and grow affluent, high-net-worth client segments. In Sri Lanka, despite significant investments in branded premium offerings, evidence suggests that the actual value perceived by customers often falls short of expectations. Past studies highlight key issues, including a lack of personalization, insufficient digital integration, reactive relationship management, and limited lifestyle benefits. Customer feedback reinforces this gap, with many clients perceiving “priority” services as symbolic rather than substantive. This research investigates how Sri Lankan banks can enhance the value proposition of their priority banking services by aligning more closely with evolving elite customer expectations. Using a mixed-method approach, the study integrates surveys and interviews with relationship managers and priority clients in certain states and private banks in Sri Lanka, supported by secondary data from reports and academic studies. Findings reveal that while customers value exclusivity and trust, true loyalty is undermined by generic service delivery and limited proactive engagement. To address these gaps, this study proposes the P.E.A.K. Model, a strategic framework emphasizing Personalization (tailored financial and lifestyle solutions), Experience Integration (seamless digital- physical journeys), Anticipation (proactive, predictive engagement), and Knowledge Empowerment (financial literacy and advisory tools). The model underscores the importance of leveraging AI- driven personalization, omnichannel CRM, and well-trained relationship managers to create a more differentiated and meaningful client experience.
Embargo
Leveraging Word Embedding for Automated Candidate Ranking in Talent Acquisition Processes
(SLIIT, 2024-12) Rasanayagam, J
Ranking the applicants who applied for a certain position in a company is mostly done manually. To ease this process, this system creates a ranking system by giving scores for each applicant based on the word embedding model trained using the past datasets. The job advertisements related to information technology fields or related to certain positions are collected and trained a model using the word embedding process. The system compares the resume of the applicant with this model and allocates a specific score for each applicant and orders them in the ascending order. Data crawling and scraping, text preprocessing and training the model are the main components in this research. The goal of this research is to collect the data of job openings related to the information technology industry and collect the job seekers information through the web scraping and crawling and train a model to rank the applicants. The crawled data is used to prepare the corpus. Python scrapy is used to prepare the crawler script for this crawling mechanism. The crawled data is then undergone for the preprocessing. Finally, the preprocessed corpus is undergone for the word embedding. Word2Vec, Gensim are some algorithms used here to train a model. This model is used to compare the resumes of each applicant and get value from the model and finally it will output a total score for each resume and then the system finally ranks the applicants based on the scores they got in ascending order.
Open Access
“AccessBIM” - A Model of Environmental Characteristics for Vision Impaired Indoor Navigation and Way Finding
(Curtin University, 2018-06) Jayakody, A
The navigation of indoor and outdoor environments play a pivotal role in the daily routine of humans. Navigation systems that provide path planning and exploration services for outdoor environments are readily available while navigation within a building is still a challenge due to limited information availability and the poor quality of GPS signals, which makes it difficult to capture characteristics within the indoor environment. Consequently, the use of GPS tracking devices for real-time map generation is not feasible. Indoor navigation is particularly difficult for people with vision impairment. According to the factsheet of the World Health Organization (WHO) as of October 2017, over 253 million people are estimated to be vision impaired: 36 million to be blind, and 217 to have poor vision. Currently, most blind and vision-impaired individuals use the white cane as an assistive tool and are often accompanied by care takers or voluntary helpers. Most modern indoor environments consist of complex architectural structures with varying arrangement of physical objects. Since retrieving indoor location information has been challenging for the vision impaired, it would be helpful if spatial information of doors, walls and staircases were made available. To address the above-mentioned problem, this thesis presents an improved schema design, an Accessible Building Information Model (AccessBIM) which could be used for generating an indoor map that could instruct vision impaired individuals in navigation, by the classification of real world objects and their locations. AccessBIM is a real-time relational database, which acts as the main component of the central system implemented to manipulate crowdsourced data such as the floor plan and architectural data along with semantic information within the built environment. The AccessBIM database stores information on the indoor arrangement of objects within buildings to facilitate the exchange and interoperability of real-time information. The database is equipped with an optimization algorithm that reduces the query execution time with the support of indexing, query re-writing, schema redesigning and a memory optimization technique introduced as “BIMcache”. vi In order to create a real-time map, the AccessBIM manipulates crowdsourced data from “smart devices” or AccessBIM users. The collection and storage of crowdsourced data, database optimization, API functions and the map construction algorithms were tested using a simulated test engine. The AccessBIM framework has the potential to play an integral role in assistive technologies related to localization and mapping, thus significantly improving the independence and quality of life for people with vision impairment whilst also decreasing the cost to the community related to support workers

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