All Outputs (8)

Leveraging contextual representations with BiLSTM-based regressor for lexical complexity prediction (2023)
Journal Article
Aziz, A., Hossain, M. A., Chy, A. N., Ullah, M. Z., & Aono, M. (2023). Leveraging contextual representations with BiLSTM-based regressor for lexical complexity prediction. Natural Language Processing Journal, 5, Article 100039. https://doi.org/10.1016/j.nlp.2023.100039

Lexical complexity prediction (LCP) determines the complexity level of words or phrases in a sentence. LCP has a significant impact on the enhancement of language translations, readability assessment, and text generation. However, the domain-specific... Read More about Leveraging contextual representations with BiLSTM-based regressor for lexical complexity prediction.

Selective Query Processing: A Risk-Sensitive Selection of Search Configurations (2023)
Journal Article
Mothe, J., & Ullah, M. Z. (2024). Selective Query Processing: A Risk-Sensitive Selection of Search Configurations. ACM transactions on information systems, 42(1), https://doi.org/10.1145/3608474

In information retrieval systems, search parameters are optimized to ensure high effectiveness based on a set of past searches and these optimized parameters are then used as the system configuration for all subsequent queries. A better approach, how... Read More about Selective Query Processing: A Risk-Sensitive Selection of Search Configurations.

Instruments and Tools to Identify Radical Textual Content (2022)
Journal Article
Mothe, J., Ullah, M. Z., Okon, G., Schweer, T., Juršėnas, A., & Mandravickaitė, J. (2022). Instruments and Tools to Identify Radical Textual Content. Information, 13(4), Article 193. https://doi.org/10.3390/info13040193

The Internet and social networks are increasingly becoming a media of extremist propaganda. On homepages, in forums or chats, extremists spread their ideologies and world views, which are often contrary to the basic liberal democratic values of the E... Read More about Instruments and Tools to Identify Radical Textual Content.

Query expansion for microblog retrieval focusing on an ensemble of features (2019)
Journal Article
Chy, A. N., Ullah, M. Z., & Aono, M. (2019). Query expansion for microblog retrieval focusing on an ensemble of features. Journal of Information Processing, 27, 61-76. https://doi.org/10.2197/ipsjjip.27.61

In microblog search, vocabulary mismatch is a persisting problem due to the brevity of tweets and frequent use of unconventional abbreviations. One way of alleviating this problem is to reformulate the query via query expansion. However, finding good... Read More about Query expansion for microblog retrieval focusing on an ensemble of features.

Learning to adaptively rank document retrieval system configurations (2018)
Journal Article
Deveaud, R., Mothe, J., Ullah, M. Z., & Nie, J. (2019). Learning to adaptively rank document retrieval system configurations. ACM transactions on information systems, 37(1), Article 3. https://doi.org/10.1145/3231937

Modern Information Retrieval (IR) systems have become more and more complex, involving a large number of parameters. For example, a system may choose from a set of possible retrieval models (BM25, language model, etc.), or various query expansion par... Read More about Learning to adaptively rank document retrieval system configurations.

Microblog Retrieval Using Ensemble of Feature Sets through Supervised Feature Selection (2017)
Journal Article
Chy, A. N., Ullah, M. Z., & Aono, M. (2017). Microblog Retrieval Using Ensemble of Feature Sets through Supervised Feature Selection. IEICE Transactions on Information and Systems, 100(4), 793-806. https://doi.org/10.1587/transinf.2016DAP0032

Microblog, especially twitter, has become an integral part of our daily life for searching latest news and events information. Due to the short length characteristics of tweets and frequent use of unconventional abbreviations, content-relevance based... Read More about Microblog Retrieval Using Ensemble of Feature Sets through Supervised Feature Selection.

A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features (2016)
Journal Article
Ullah, M. Z., & Aono, M. (2016). A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features. IEICE Transactions on Information and Systems, 99(12), 3090-3100. https://doi.org/10.1587/transinf.2016EDP7190

Web search queries are usually vague, ambiguous, or tend to have multiple intents. Users have different search intents while issuing the same query. Understanding the intents through mining subtopics underlying a query has gained much interest in rec... Read More about A bipartite graph-based ranking approach to query subtopics diversification focused on word embedding features.

Estimating a Ranked List of Human Genetic Diseases by Associating Phenotype-Gene with Gene-Disease Bipartite Graphs (2015)
Journal Article
Ullah, M. Z., Aono, M., & Seddiqui, M. H. (2015). Estimating a Ranked List of Human Genetic Diseases by Associating Phenotype-Gene with Gene-Disease Bipartite Graphs. ACM transactions on intelligent systems and technology, 6(4), Article 56. https://doi.org/10.1145/2700487

With vast amounts of medical knowledge available on the Internet, it is becoming increasingly practical to help doctors in clinical diagnostics by suggesting plausible diseases predicted by applying data and text mining technologies. Recently, Genome... Read More about Estimating a Ranked List of Human Genetic Diseases by Associating Phenotype-Gene with Gene-Disease Bipartite Graphs.