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Harikrishnan C

dblp:371/7350 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2024
0000-0003-3416-9261ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Databases, data management, data science and information retrieval · 1 · 1 first-author · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval › interactive information retrieval › conversational information seeking
conversational search
0.812024
Augmenting Keyword-based Search in Mobile Applications Using LLMs · WSDM 2024
Information retrieval › web search
mobile search
0.812024
Augmenting Keyword-based Search in Mobile Applications Using LLMs · WSDM 2024
Information retrieval
retrieval models
0.812024
Augmenting Keyword-based Search in Mobile Applications Using LLMs · WSDM 2024
Information retrieval
search engines
0.812024
Augmenting Keyword-based Search in Mobile Applications Using LLMs · WSDM 2024

Methods — techniques the papers use, named apart from their topics

large language model · 0.8
YearPublicationVenuePosition
2024 Augmenting Keyword-based Search in Mobile Applications Using LLMs
abstract
Search in mobile applications has traditionally been keyword driven and limited to simple queries, such as searching for product names, even when the apps support much richer, transactional experiences. On the other hand, search on the web has evolved into queries that are complex, objective-based and most often in natural language. The recent advances in Generative AI make it possible to bring the power of web-like, conversational searches into mobile applications. In this talk, we present the various problems, opportunities and challenges in harnessing LLMs to augment the traditional search experience in mobile applications.
Harikrishnan C, Giridhar Sreenivasa Murthy, Kumar Rangarajan
WSDM1