26 citations · 38 across the 5 of their papers we have counts for
7 papers
On the Replicability of Combining Word Embeddings and Retrieval Models
Luca Papariello, Alexandros Bampoulidis, Mihai Lupu
We replicate recent experiments attempting to demonstrate an attractive hypothesis about the use of the Fisher kernel framework and mixture models for aggregating word embeddings t…
An Abstract View on the De-anonymization Process
Alexandros Bampoulidis, Mihai Lupu
Over the recent years, the availability of datasets containing personal, but anonymized information has been continuously increasing. Extensive research has revealed that such data…
Addressing Cross-Lingual Word Sense Disambiguation on Low-Density Languages: Application to Persian
Navid Rekabsaz, Mihai Lupu, Allan Hanbury +1
We explore the use of unsupervised methods in Cross-Lingual Word Sense Disambiguation (CL-WSD) with the application of English to Persian. Our proposed approach targets the languag…
Toward Incorporation of Relevant Documents in word2vec
Navid Rekabsaz, Bhaskar Mitra, Mihai Lupu +1
Recent advances in neural word embedding provide significant benefit to various information retrieval tasks. However as shown by recent studies, adapting the embedding models for t…
Character-based Neural Embeddings for Tweet Clustering
Svitlana Vakulenko, Lyndon Nixon, Mihai Lupu
In this paper we show how the performance of tweet clustering can be improved by leveraging character-based neural networks. The proposed approach overcomes the limitations related…
Volatility Prediction using Financial Disclosures Sentiments with Word Embedding-based IR Models
Navid Rekabsaz, Mihai Lupu, Artem Baklanov +3
Volatility prediction--an essential concept in financial markets--has recently been addressed using sentiment analysis methods. We investigate the sentiment of annual disclosures o…
Uncertainty in Neural Network Word Embedding: Exploration of Threshold for Similarity
Navid Rekabsaz, Mihai Lupu, Allan Hanbury
Word embedding, specially with its recent developments, promises a quantification of the similarity between terms. However, it is not clear to which extent this similarity value ca…