Daniel Tunkelang
Mountain View, California, United States
38K followers
500+ connections
About
Search, recommender systems, machine learning / AI, LLMs / RAG, data science. LinkedIn /…
Services
Articles by Daniel
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Navigating the Pareto Frontier
Navigating the Pareto Frontier
Traditional search applications retrieve relevant results, score them based on desirability, and present them in ranked…
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Precision, Recall, and Desirability: A Deep Dive
Precision, Recall, and Desirability: A Deep Dive
This post expands on my previous discussion of “Precision, Recall, and Desirability,” diving deeper into defining…
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ChatGPT, Are You Just Telling Me What I Want to Hear?
ChatGPT, Are You Just Telling Me What I Want to Hear?
These days, the Turing Test — which Turing originally called the “imitation game” — feels hopelessly outdated. With…
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Not All Recall is Created Equal
Not All Recall is Created Equal
Search application developers constantly navigate tradeoffs, particularly between precision and recall. Precision…
1 Comment -
To Bot or Not to Bot: It Depends on the Question
To Bot or Not to Bot: It Depends on the Question
I was one of Quora’s earliest users. I earned Top Writer status for several years and even made some money through…
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Ground Truth: A Useful Fiction
Ground Truth: A Useful Fiction
A key concern about AI is that models “hallucinate” — technical jargon for saying that they make up things that look…
5 Comments -
Conjunction, Disjunction, What’s Your Function?
Conjunction, Disjunction, What’s Your Function?
Like many folks of my generation, I grew up on Schoolhouse Rock, a series of animated educational shorts that aired…
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Modeling Queries as Bags of Documents
Modeling Queries as Bags of Documents
Last week, I had the honor of presenting “Modeling Queries as Bags of Documents” at Search Solutions 2024 with Aritra…
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Documents, Queries, and Categories
Documents, Queries, and Categories
I have published a number of posts and presentations about the bag-of-documents model, which essentially represents…
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Where Do Categories Come From?
Where Do Categories Come From?
In my previous post, I argued that categories are fundamental for search applications. I characterized a robust set of…
1 Comment
Activity
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The Loomatics are running the asylum.
The Loomatics are running the asylum.
Shared by Daniel Tunkelang
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I'm very curious to see how Meta's AI-enabled coding interview experiment plays out. Indeed, if Meta expects engineers to use AI to write code, then…
I'm very curious to see how Meta's AI-enabled coding interview experiment plays out. Indeed, if Meta expects engineers to use AI to write code, then…
Shared by Daniel Tunkelang
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RIP, Tom Lehrer. Thank you for enriching my life -- from childhood through adulthood -- with your songs.
RIP, Tom Lehrer. Thank you for enriching my life -- from childhood through adulthood -- with your songs.
Shared by Daniel Tunkelang
Experience
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Self
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Education
Publications
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The Role of Network Distance in Linkedin People Search
37th Annual International ACM SIGIR Conference (SIGIR 2014)
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Web Science: How is it different?
ACM Web Science 2014 Conference (WebSci 2014)
See publicationKeynote Address at ACM Web Science 2014 Conference (WebSci 2014)
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Symposium on Human–Computer Information Retrieval
Journal of Big Data
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Find and be Found: Information Retrieval at LinkedIn
36th Annual International ACM SIGIR Conference (SIGIR 2013)
Invited talk at the 36th Annual International ACM SIGIR Conference (SIGIR 2013)
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Introduction to Special Issue on Human-Computer Information Retrieval
Journal of Information Processing & Management
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Content, Connections, and Context
6th ACM International Conference on Recommender Systems (RecSys 2012)
See publicationKeynote at Workshop on Recommender Systems and the Social Web (RSWeb 2012)
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Data By The People, For The People
21st ACM International Conference on Information and Knowledge Management (CIKM 2012)
See publicationInvited Talk at the 21st ACM International Conference on Information and Knowledge Management (CIKM 2012)
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Recommendations as a Conversation with the User
5th ACM International Conference on Recommender Systems (RecSys 2011)
See publicationTutorial exploring role of recommendations as part of a conversation between user and information-seeking system.
Patents
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Search Result Identification Using Vector Aggregation
Issued US 12,124,522
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Leveraging A Social Graph For Use With Electronic Messaging
Issued US 9,971,993
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Method and System for Semantic Search against a Document Collection
Issued US 9,710,518
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Method and System for Semantic Search against a Document Collection
Issued US 9,116,948
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System and Method for Measuring the Quality of Document Sets
Issued US 8,874,549
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Method and System for Information Retrieval with Clustering
Issued US 8,676,802
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Method and System for Semantic Search Against a Document Collection
Issued US 8,473,503
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System and Method for Measuring the Quality of Document Sets
Issued US 8,219,593
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System and Method for Measuring the Quality of Document Sets
Issued US 8,051,073
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System and Method for Measuring the Quality of Document Sets
Issued US 8,051,084
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System and Method for Measuring the Quality of Document Sets
Issued US 8,024,327
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System and Method for Measuring the Quality of Document Sets
Issued US 8,005,643
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Hierarchical Data-Driven Navigation System and Method for Information Retrieval
Issued US 7,912,823
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Hierarchical Data-Driven Navigation System and Method for Information Retrieval
Issued US 7,035,864
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Applying Numerical Approximation to General Graph Drawing
Issued US 5,995,114
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Identifying Members of a Small and Medium Business Segment
Filed US 14/318,326
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Techniques For Identifying And Presenting Connection Paths
Filed US 13/548,957
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Techniques For Identifying And Presenting Connection Paths
Filed US 13/482,884
Languages
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Spanish
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French
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Italian
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Portuguese
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German
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Join now to viewMore activity by Daniel
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He's got big balls and she's got big balls But South Park's got the biggest balls of them all.
He's got big balls and she's got big balls But South Park's got the biggest balls of them all.
Shared by Daniel Tunkelang
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