no code implementations • LREC 2020 • Dimuthu Lakmal, Surangika Ranathunga, Saman Peramuna, Indu Herath
This paper presents the first ever comprehensive evaluation of different types of word embeddings for Sinhala language.
no code implementations • 27 May 2018 • Keet Sugathadasa, Buddhi Ayesha, Nisansa de Silva, Amal Shehan Perera, Vindula Jayawardana, Dimuthu Lakmal, Madhavi Perera
The ensemble model built in this study, shows a significantly higher accuracy level, which indeed proves the need for incorporation of domain specific semantic similarity measures into the information retrieval process.
no code implementations • 9 Sep 2017 • Vindula Jayawardana, Dimuthu Lakmal, Nisansa de Silva, Amal Shehan Perera, Keet Sugathadasa, Buddhi Ayesha, Madhavi Perera
With the use of word embeddings in the field of natural language processing, it became a popular topic due to its ability to cope up with semantic sensitivity.
no code implementations • 8 Jun 2017 • Vindula Jayawardana, Dimuthu Lakmal, Nisansa de Silva, Amal Shehan Perera, Keet Sugathadasa, Buddhi Ayesha
Selecting a representative vector for a set of vectors is a very common requirement in many algorithmic tasks.
no code implementations • 6 Jun 2017 • Keet Sugathadasa, Buddhi Ayesha, Nisansa de Silva, Amal Shehan Perera, Vindula Jayawardana, Dimuthu Lakmal, Madhavi Perera
Semantic similarity measures are an important part in Natural Language Processing tasks.