Search Results for author: Amal Shehan Perera

Found 13 papers, 0 papers with code

Legal Case Winning Party Prediction With Domain Specific Auxiliary Models

no code implementations ROCLING 2022 Sahan Jayasinghe, Lakith Rambukkanage, Ashan Silva, Nisansa de Silva, Amal Shehan Perera

The model is built with and experimented using legal domain specific sub-models to provide more visibility to the final model, along with other variations.

Sentence Sentence Embedding +1

User Localization Based on Call Detail Records

no code implementations20 Aug 2021 Buddhi Ayesha, Bhagya Jeewanthi, Charith Chitraranjan, Amal Shehan Perera, Amal S. Kumarage

However, one of the main issues in using CDR data is that it is difficult to identify the precise location of the user due to the low spacial resolution of the data and other artifacts such as the load sharing effect.

Effective Approach to Develop a Sentiment Annotator For Legal Domain in a Low Resource Setting

no code implementations PACLIC 2020 Gathika Ratnayaka, Nisansa de Silva, Amal Shehan Perera, Ramesh Pathirana

Analyzing the sentiments of legal opinions available in Legal Opinion Texts can facilitate several use cases such as legal judgement prediction, contradictory statements identification and party-based sentiment analysis.

Sentiment Analysis

Shift-of-Perspective Identification Within Legal Cases

no code implementations6 Jun 2019 Gathika Ratnayaka, Thejan Rupasinghe, Nisansa de Silva, Viraj Salaka Gamage, Menuka Warushavithana, Amal Shehan Perera

Therefore, the process of automatic information extraction from documents containing legal opinions related to court cases can be considered to be of significant importance.

Open Information Extraction Sentiment Analysis

Identifying Relationships Among Sentences in Court Case Transcripts Using Discourse Relations

no code implementations10 Sep 2018 Gathika Ratnayaka, Thejan Rupasinghe, Nisansa de Silva, Menuka Warushavithana, Viraj Gamage, Amal Shehan Perera

To the best of our knowledge, this is the first study where discourse relationships between sentences have been used to determine relationships among sentences in legal court case transcripts.

Legal Document Retrieval using Document Vector Embeddings and Deep Learning

no code implementations27 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 implementations9 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

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