What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- The Internet
- Information retrieval
Iadh Ounis mainly investigates Information retrieval, Data mining, Artificial intelligence, Query expansion and Ranking.
His biological study spans a wide range of topics, including World Wide Web and Information needs.
His studies deal with areas such as Scalability, Training set, Anchor text, Word lists by frequency and Term as well as Data mining.
Iadh Ounis combines subjects such as Machine learning, Baseline and Natural language processing with his study of Artificial intelligence.
His Query expansion research is multidisciplinary, relying on both Concept search and Web query classification.
His work deals with themes such as Sargable and Query optimization, which intersect with Web query classification.
His most cited work include:
- Exploiting query reformulations for web search result diversification (365 citations)
- Overview of the TREC 2006 Blog Track (246 citations)
- Terrier information retrieval platform (237 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Information retrieval, Artificial intelligence, Data mining, World Wide Web and Ranking.
His Information retrieval study frequently links to other fields, such as Ranking.
His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning, Recommender system and Natural language processing.
His Data mining research includes elements of Term and Search engine indexing.
His research in Social media and Blogosphere are components of World Wide Web.
His study on Query expansion also encompasses disciplines like
- Query optimization, which have a strong connection to Sargable,
- Query language and related RDF query language.
He most often published in these fields:
- Information retrieval (60.39%)
- Artificial intelligence (22.16%)
- Data mining (16.62%)
What were the highlights of his more recent work (between 2017-2021)?
- Artificial intelligence (22.16%)
- Information retrieval (60.39%)
- Machine learning (11.91%)
In recent papers he was focusing on the following fields of study:
Iadh Ounis mostly deals with Artificial intelligence, Information retrieval, Machine learning, Recommender system and Classifier.
The Artificial intelligence study combines topics in areas such as Ranking and Natural language processing.
His study of Ranking is a part of Information retrieval.
The various areas that Iadh Ounis examines in his Machine learning study include Feedback loop and Bayesian probability.
His Recommender system study integrates concerns from other disciplines, such as Recurrent neural network and Leverage.
His Classifier research incorporates elements of Active learning, Information sensitivity and Training set.
Between 2017 and 2021, his most popular works were:
- Using word embeddings in Twitter election classification (66 citations)
- A Contextual Attention Recurrent Architecture for Context-Aware Venue Recommendation (43 citations)
- Regional Sentiment Bias in Social Media Reporting During Crises (10 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- The Internet
- Machine learning
His main research concerns Artificial intelligence, Information retrieval, Social media, Recommender system and Machine learning.
Iadh Ounis works in the field of Information retrieval, namely Automatic summarization.
Iadh Ounis has researched Social media in several fields, including Topic model and Data science.
His Recommender system study integrates concerns from other disciplines, such as Recurrent neural network, Human–computer interaction and Similarity.
In general Machine learning study, his work on Ranking and Collaborative filtering often relates to the realm of Simple and Space, thereby connecting several areas of interest.
His studies in Ranking integrate themes in fields like Predictive modelling and Selection.
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