Pyserini: A Python toolkit for reproducible information retrieval research with sparse and dense representations
Pyserini is a Python toolkit for reproducible information retrieval research with sparse and
dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage …
dense representations. It aims to provide effective, reproducible, and easy-to-use first-stage …
[图书][B] Pretrained transformers for text ranking: Bert and beyond
The goal of text ranking is to generate an ordered list of texts retrieved from a corpus in
response to a query. Although the most common formulation of text ranking is search …
response to a query. Although the most common formulation of text ranking is search …
Anserini: Reproducible ranking baselines using Lucene
This work tackles the perennial problem of reproducible baselines in information retrieval
research, focusing on bag-of-words ranking models. Although academic information …
research, focusing on bag-of-words ranking models. Although academic information …
Declarative experimentation in information retrieval using PyTerrier
C Macdonald, N Tonellotto - Proceedings of the 2020 ACM SIGIR on …, 2020 - dl.acm.org
The advent of deep machine learning platforms such as Tensorflow and Pytorch, developed
in expressive high-level languages such as Python, have allowed more expressive …
in expressive high-level languages such as Python, have allowed more expressive …
Reduce, reuse, recycle: Green information retrieval research
Recent advances in Information Retrieval utilise energy-intensive hardware to produce state-
of-the-art results. In areas of research highly related to Information Retrieval, such as Natural …
of-the-art results. In areas of research highly related to Information Retrieval, such as Natural …
PyTerrier: Declarative experimentation in Python from BM25 to dense retrieval
PyTerrier is a Python-based retrieval framework for expressing simple and complex
information retrieval (IR) pipelines in a declarative manner. While making use of the long …
information retrieval (IR) pipelines in a declarative manner. While making use of the long …
BERT-QE: contextualized query expansion for document re-ranking
Query expansion aims to mitigate the mismatch between the language used in a query and
in a document. However, query expansion methods can suffer from introducing non-relevant …
in a document. However, query expansion methods can suffer from introducing non-relevant …
Shopping queries dataset: A large-scale ESCI benchmark for improving product search
Improving the quality of search results can significantly enhance users experience and
engagement with search engines. In spite of several recent advancements in the fields of …
engagement with search engines. In spite of several recent advancements in the fields of …
Using word embeddings in twitter election classification
Word embeddings and convolutional neural networks (CNN) have attracted extensive
attention in various classification tasks for Twitter, eg sentiment classification. However, the …
attention in various classification tasks for Twitter, eg sentiment classification. However, the …
[HTML][HTML] Overview of the TREC 2017 precision medicine track
K Roberts, D Demner-Fushman… - The... text REtrieval …, 2017 - ncbi.nlm.nih.gov
For many complex diseases, there is no “one size fits all” solutions for patients with a
particular diagnosis. The proper treatment for a patient depends upon genetic …
particular diagnosis. The proper treatment for a patient depends upon genetic …