Designing Search-as-Learning Systems

At the core of Search-as-Learning (SAL), as a sub-field of Interactive Information Retrieval (IIR), is exploring how people use search engines to acquire knowledge. Inherently interactive, the knowledge acquisition process via a search system involves learners posing queries, analyzing content, and incorporating novel knowledge. Being this...

Towards Robust Automatic Question Generation For Learning

Questions are critical for information-seeking and learning. Automatic Question Generation (AQG) involves the subjects of Information Retrieval (IR) and Natural Language Processing (NLP), and focuses on automatically creating questions for various applications, subjects which have been studied for decades. In this thesis, we study how to create...

Designing and Diagnosing Models for Conversational Search and Recommendation

Conversational search is a sub-field of Information Retrieval (IR) that focuses on solving information needs through natural language conversations. Searching for information is an inherently interactive task, and conversations offer a promising solution. One that might change the current search paradigm. In this thesis, we focus on retrieval...

Examining the Effectiveness of Collaborative Search Engines