Self-supervised sentiment classification based on semantic similarity measures and contextual embedding using metaheuristic optimizer
In recent years, considerable research attention has been paid to supervised machine
learning methods for Sentiment Analysis (SA). The performance of these methods heavily …
learning methods for Sentiment Analysis (SA). The performance of these methods heavily …
On the analysis and evaluation of information retrieval models for social book search
Abstract Social Book Search (SBS) studies how the Social Web impacts book retrieval. This
impact is studied in two steps. In this first step, called the baseline run, the search index …
impact is studied in two steps. In this first step, called the baseline run, the search index …
Sstsa: A self-supervised topic sentiment analysis using semantic similarity measures and transformers
The exponentially increasing amount of data generated by the public on social media
platforms is a precious source of information. It can be used to find the topics and analyze …
platforms is a precious source of information. It can be used to find the topics and analyze …
On smoothing and scaling language model for sentiment based information retrieval
Sentiment analysis or opinion mining refers to the discovery of sentiment information within
textual documents, tweets, or review posts. This field has emerged with the social media …
textual documents, tweets, or review posts. This field has emerged with the social media …
Improving social book search using structure semantics, bibliographic descriptions and social metadata
Abstract Social Book Search is an Information Retrieval (IR) approach that studies the
impact of the Social Web on book retrieval. To understand this impact, it is necessary to …
impact of the Social Web on book retrieval. To understand this impact, it is necessary to …
A book recommendation system considering contents and emotions of user interests
T Fujimoto, H Murakami - 2022 12th International Congress on …, 2022 - ieeexplore.ieee.org
Although the benefits of reading are widely recognized, many people seldom read even
though they often claim to have interest in reading. Since conventional book …
though they often claim to have interest in reading. Since conventional book …
Modelling social readers: novel tools for addressing reception from online book reviews
P Holur, S Shahsavari… - Royal Society …, 2021 - royalsocietypublishing.org
Social reading sites offer an opportunity to capture a segment of readers' responses to
literature, while data-driven analysis of these responses can provide new critical insight into …
literature, while data-driven analysis of these responses can provide new critical insight into …
On the current state of query formulation for book search
The role of formulating a well-defined query in the retrieval of relevant search results is well-
known to the users of an Information Retrieval (IR) system. Researchers have experimented …
known to the users of an Information Retrieval (IR) system. Researchers have experimented …
[PDF][PDF] Pseudo-Relevance Feedback Combining Statistical and Semantic Term Extraction for Searching Arabic Documents.
Pseudo-relevance feedback (PRF) is an effective query expansion method for searching
candidate terms based on top-ranked documents. PRF uses a statistical approach that relies …
candidate terms based on top-ranked documents. PRF uses a statistical approach that relies …
Sentiment intensity prediction using neural word embeddings
Sentiment analysis is central to the process of mining opinions and attitudes from online
texts. While much attention has been paid to the sentiment classification problem, much less …
texts. While much attention has been paid to the sentiment classification problem, much less …