Embedding-based retrieval in graph-based recommendation has shown great improvements over traditional graph walk retrieval methods, and has been adopted in large-scale industry applications such as friend recommendations [16]. However, it is not without ...

Query expansion has been widely used to improve the search results of first-stage retrievers, yet its influence on second-stage, cross-encoder rankers remains under-explored. A recent study shows that current expansion techniques benefit weaker models ...

While dense retrieval methods have made significant advancements, sparse retrieval techniques continue to offer advantages in terms of interpretability and generalizability. However, query-document term mismatch in sparse retrieval persists, rendering it ...

Most conversational passage retrieval systems try to resolve conversational dependencies by using an intermediate query resolution step. To do so, they synthesize conversational data or assume the availability of large-scale question rewriting datasets. ...

Humans are accustomed to autonomously associating prior knowledge with the text in a query when answering questions. However, for machines lacking cognition and common sense, a query is merely a combination of some words. Although we can enrich the ...

There is a long history of work on using relevance feedback for ad hoc document retrieval. The main types of relevance feedback studied thus far are for documents, passages and terms. We explore the merits of using relevance feedback provided for ...

Conversational search allows a user to interact with a search system in multiple turns. A query is strongly dependent on the conversation context. An effective way to improve retrieval effectiveness is to expand the current query with historical ...

This article presents a new query expansion (QE) method aiming to tackle term mismatch in information retrieval (IR). Previous research showed that selecting good expansion terms which do not hurt retrieval effectiveness remains an open and challenging ...

Despite the advantages of their low-resource settings, traditional sparse retrievers depend on exact matching approaches between high-dimensional bag-of-words (BoW) representations of both the queries and the collection. As a result, retrieval ...

The color of the products is one of the most prevalent aspects in many e-commerce domains, and it is one of the decisive purchasing factors. Besides having thousands of color variations and shades, many brands continuously develop proprietary colors and ...

Pseudo-relevance feedback mechanisms have long served as an effective technique to improve the retrieval effectiveness in information retrieval. Recently, large pre-trained language models, such as T5 and BERT, have shown a strong capacity to capture ...

Building a retrieval system with lifelogging data is more complicated than with ordinary data due to the redundancies, blurriness, massive amount of data, various sources of information accompanying lifelogging data, and especially the ad-hoc nature of ...

Patents are critical intellectual assets for any business. With the rapid increase in the patent filings, patent prior art retrieval has become an important task. The goal of the prior art retrieval is to find documents relevant to a patent application. ...

To assist the COVID-19 focused researchers in life science and healthcare in understanding the pandemic, we present an exploratory information retrieval system called RCES. The system employs a previously developed EVE (Explainable Vector-based ...

Pseudo-relevance feedback mechanisms, from Rocchio to the relevance models, have shown the usefulness of expanding and reweighting the users' initial queries using information occurring in an initial set of retrieved documents, known as the pseudo-...

With Web 2.0, there has been exponential growth in the number of Web users and the volume of Web content. Most of these users are not only consumers of the information but also generators of it. People express themselves here in colloquial languages, but ...

A study conducted by the International Data Corporation predicted that by the year 2021, the total amount of digital information resources would have reached the 40 zettabyte mark [2]. According to a rule formulated by Merrill Lynch, 80 to 90% of these ...

Various researchers have recently explored the impact of different types of biases on information retrieval tasks such as ad hoc retrieval and question answering. While the impact of bias needs to be controlled in order to avoid increased prejudices, the ...

Web search engines are today considered to be the primary tool to assist and empower learners in finding information relevant to their learning goals- be it learning something new, improving their existing skills, or just fulfilling a curiosity. While ...

A significant number of event-related queries are issued in Web search. In this paper, we seek to improve retrieval performance by leveraging events and specifically target the classic task of query expansion. We propose a method to expand an event-...