Rethinking search: making domain experts out of dilettantes
When experiencing an information need, users want to engage with a domain expert, but
often turn to an information retrieval system, such as a search engine, instead. Classical …
often turn to an information retrieval system, such as a search engine, instead. Classical …
Where are the facts? searching for fact-checked information to alleviate the spread of fake news
Although many fact-checking systems have been developed in academia and industry, fake
news is still proliferating on social media. These systems mostly focus on fact-checking but …
news is still proliferating on social media. These systems mostly focus on fact-checking but …
Contextualized embeddings based transformer encoder for sentence similarity modeling in answer selection task
Word embeddings that consider context have attracted great attention for various natural
language processing tasks in recent years. In this paper, we utilize contextualized word …
language processing tasks in recent years. In this paper, we utilize contextualized word …
Curriculum learning strategies for IR: An empirical study on conversation response ranking
Neural ranking models are traditionally trained on a series of random batches, sampled
uniformly from the entire training set. Curriculum learning has recently been shown to …
uniformly from the entire training set. Curriculum learning has recently been shown to …
Metaphor detection via linguistics enhanced Siamese network
S Zhang, Y Liu - Proceedings of the 29th International Conference …, 2022 - aclanthology.org
In this paper we present MisNet, a novel model for word level metaphor detection. MisNet
converts two linguistic rules, ie, Metaphor Identification Procedure (MIP) and Selectional …
converts two linguistic rules, ie, Metaphor Identification Procedure (MIP) and Selectional …
A hybrid approach of Weighted Fine-Tuned BERT extraction with deep Siamese Bi–LSTM model for semantic text similarity identification
The conventional semantic text-similarity methods requires high amount of trained labeled
data and also human interventions. Generally, it neglects the contextual-information and …
data and also human interventions. Generally, it neglects the contextual-information and …
Contextualized knowledge-aware attentive neural network: Enhancing answer selection with knowledge
Answer selection, which is involved in many natural language processing applications, such
as dialog systems and question answering (QA), is an important yet challenging task in …
as dialog systems and question answering (QA), is an important yet challenging task in …
Towards Boosting LLMs-driven Relevance Modeling with Progressive Retrieved Behavior-augmented Prompting
Relevance modeling is a critical component for enhancing user experience in search
engines, with the primary objective of identifying items that align with users' queries …
engines, with the primary objective of identifying items that align with users' queries …
Deep multimodal learning for information retrieval
Information retrieval (IR) is a fundamental technique that aims to acquire information from a
collection of documents, web pages, or other sources. While traditional text-based IR has …
collection of documents, web pages, or other sources. While traditional text-based IR has …
Answer ranking for product-related questions via multiple semantic relations modeling
Many E-commerce sites now offer product-specific question answering platforms for users to
communicate with each other by posting and answering questions during online shopping …
communicate with each other by posting and answering questions during online shopping …