Word Embedding Evaluation for Sinhala

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.

Part-Of-Speech Tagging POS +3

Legal Document Retrieval using Document Vector Embeddings and Deep Learning

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.

Information Retrieval Retrieval +4

Semi-Supervised Instance Population of an Ontology using Word Vector Embeddings

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.

Management Word Embeddings

Deriving a Representative Vector for Ontology Classes with Instance Word Vector Embeddings

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.

Synergistic Union of Word2Vec and Lexicon for Domain Specific Semantic Similarity

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.

Lemmatization Semantic Similarity +1