Question Answering (QA) systems based on Information Retrieval return precise answers to
natural language questions, extracting relevant sentences from document collections …

With the rapid growth of textual content on the Internet, automatic text categorization is a
comparatively more effective solution in information organization and knowledge …

Multi-label classification assigns multiple labels to each document concurrently. Many real-
world classification problems tend to employ high-dimensional label spaces, which can be …

We propose a novel text classification model, which aims to improve the performance of
Arabic text classification using machine learning techniques. One of the effective solutions in …

Multi-label text categorization refers to the problem of assigning each document to a subset
of categories by means of multi-label learning algorithms. Unlike English and most other …

Searching for relevant material that satisfies the information need of a user, within a large
document collection is a critical activity for web search engines. Query Expansion …

TF-IDF is one of the most popular term-weighting schemes, and is applied by search
engines, recommender systems, and user modeling engines. With regard to user modeling …

The importance of query performance prediction has been widely acknowledged in the
literature, especially for query expansion, refinement, and interpolating different retrieval …

The effectiveness of query expansion methods depends essentially on identifying good
candidates, or prospects, semantically related to query terms. Word embeddings have been …

Exploratory search is characterized by a user's uncertainty towards a complex information
seeking task. A user conducting such a search in an information retrieval (IR) system may …