Tootfinder

Can we predict QPP? An approach based on multivariate outliers
Adrian-Gabriel Chifu, S\'ebastien D\'ejean, Moncef Garouani, Josiane Mothe, Di\'ego Ortiz, Md Zia Ullah
https://arxiv.org/abs/2402.16875

Can we predict QPP? An approach based on multivariate outliers
Query performance prediction (QPP) aims to forecast the effectiveness of a search engine across a range of queries and documents. While state-of-the-art predictors offer a certain level of precision, their accuracy is not flawless. Prior research has recognized the challenges inherent in QPP but often lacks a thorough qualitative analysis. In this paper, we delve into QPP by examining the factors that influence the predictability of query performance accuracy. We propose the working hypothesis …

This https://arxiv.org/abs/2404.09109 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

Optimizing Disjunctive Queries with Tagged Execution
Despite decades of research into query optimization, optimizing queries with disjunctive predicate expressions remains a challenge. Solutions employed by existing systems (if any) are often simplistic and lead to much redundant work being performed by the execution engine. To address these problems, we propose a novel form of query execution called tagged execution. Tagged execution groups tuples into subrelations based on which predicates in the query they satisfy (or don't satisfy) and tags t…

Cognitively Biased Users Interacting with Algorithmically Biased Results in Whole-Session Search on Controversial Topics
Ben Wang, Jiqun Liu
https://arxiv.org/abs/2403.17286

Cognitively Biased Users Interacting with Algorithmically Biased Results in Whole-Session Search on Controversial Topics
When interacting with information retrieval (IR) systems, users, affected by confirmation biases, tend to select search results that confirm their existing beliefs on socially significant contentious issues. To understand the judgments and attitude changes of users searching online, our study examined how cognitively biased users interact with algorithmically biased search engine result pages (SERPs). We designed three-query search sessions on debated topics under various bias conditions. We re…

ByteCard: Enhancing Data Warehousing with Learned Cardinality Estimation
Yuxing Han, Haoyu Wang, Lixiang Chen, Yifeng Dong, Xing Chen, Benquan Yu, Chengcheng Yang, Weining Qian
https://arxiv.org/abs/2403.16110

ByteCard: Enhancing Data Warehousing with Learned Cardinality Estimation
Cardinality estimation is a critical component and a longstanding challenge in modern data warehouses. ByteHouse, ByteDance's cloud-native engine for big data analysis in exabyte-scale environments, serves numerous internal decision-making business scenarios. With the increasing demand of ByteHouse, cardinality estimation becomes the bottleneck for efficiently processing queries. Specifically, the existing query optimizer of ByteHouse uses the traditional Selinger-like cardinality estimator, wh…

Great! #Google has a meta-fact check search engine!
This query returns results in all languages; the default is to return only your browser language, but you can change between them and other languages.
h/t/ @…

This https://arxiv.org/abs/2312.16735 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

Flock: A Low-Cost Streaming Query Engine on FaaS Platforms
Existing serverless data analytics systems rely on external storage services like S3 for data shuffling and communication between cloud functions. While this approach provides the elasticity benefits of serverless computing, it incurs additional latency and cost overheads. We present Flock, a novel cloud-native streaming query engine that leverages the on-demand scalability of FaaS platforms for real-time data analytics. Flock utilizes function invocation payloads for efficient data exchange, e…

Polars is a lightning fast DataFrame library/in-memory query engine with parallel execution and cache efficiency. And now you can use is with the tidyverse syntax: #rstats

Great! #Google has a meta-fact check search engine!
This query returns results in all languages; the default is to return only your browser language, but you can change between them and other languages.
h/t/ @…

GenSERP: Large Language Models for Whole Page Presentation
Zhenning Zhang, Yunan Zhang, Suyu Ge, Guangwei Weng, Mridu Narang, Xia Song, Saurabh Tiwary
https://arxiv.org/abs/2402.14301

GenSERP: Large Language Models for Whole Page Presentation
The advent of large language models (LLMs) brings an opportunity to minimize the effort in search engine result page (SERP) organization. In this paper, we propose GenSERP, a framework that leverages LLMs with vision in a few-shot setting to dynamically organize intermediate search results, including generated chat answers, website snippets, multimedia data, knowledge panels into a coherent SERP layout based on a user's query. Our approach has three main stages: (1) An information gathering pha…

This https://arxiv.org/abs/2303.18086 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csCR_…

Differentially Private Stream Processing at Scale
We design, to the best of our knowledge, the first differentially private (DP) stream aggregation processing system at scale. Our system -- Differential Privacy SQL Pipelines (DP-SQLP) -- is built using a streaming framework similar to Spark streaming, and is built on top of the Spanner database and the F1 query engine from Google. Towards designing DP-SQLP we make both algorithmic and systemic advances, namely, we (i) design a novel (user-level) DP key selection algorithm that can operate on…

This https://arxiv.org/abs/2402.14301 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csIR_…

GenSERP: Large Language Models for Whole Page Presentation
The advent of large language models (LLMs) brings an opportunity to minimize the effort in search engine result page (SERP) organization. In this paper, we propose GenSERP, a framework that leverages LLMs with vision in a few-shot setting to dynamically organize intermediate search results, including generated chat answers, website snippets, multimedia data, knowledge panels into a coherent SERP layout based on a user's query. Our approach has three main stages: (1) An information gathering pha…

This https://arxiv.org/abs/2401.15479 has been replaced.
link: https://scholar.google.com/scholar?q=a

Navigating the Post-API Dilemma Search Engine Results Pages Present a Biased View of Social Media Data
Recent decisions to discontinue access to social media APIs are having detrimental effects on Internet research and the field of computational social science as a whole. This lack of access to data has been dubbed the Post-API era of Internet research. Fortunately, popular search engines have the means to crawl, capture, and surface social media data on their Search Engine Results Pages (SERP) if provided the proper search query, and may provide a solution to this dilemma. In the present work w…

This https://arxiv.org/abs/2403.16110 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

ByteCard: Enhancing ByteDance's Data Warehouse with Learned Cardinality Estimation
Cardinality estimation is a critical component and a longstanding challenge in modern data warehouses. ByteHouse, ByteDance's cloud-native engine for extensive data analysis in exabyte-scale environments, serves numerous internal decision-making business scenarios. With the increasing demand for ByteHouse, cardinality estimation becomes the bottleneck for efficiently processing queries. Specifically, the existing query optimizer of ByteHouse uses the traditional Selinger-like cardinality estima…

Search Intenion Network for Personalized Query Auto-Completion in E-Commerce
Wei Bao, Mi Zhang, Tao Zhang, Chengfu Huo
https://arxiv.org/abs/2403.02609 htt…

Search Intenion Network for Personalized Query Auto-Completion in E-Commerce
Query Auto-Completion(QAC), as an important part of the modern search engine, plays a key role in complementing user queries and helping them refine their search intentions.Today's QAC systems in real-world scenarios face two major challenges:1)intention equivocality(IE): during the user's typing process,the prefix often contains a combination of characters and subwords, which makes the current intention ambiguous and difficult to model.2)intention transfer (IT):previous works make personalized…

This https://arxiv.org/abs/2311.02206 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

Modern Datalog on the GPU
Modern deductive database engines (e.g., LogicBlox and Soufflé) enable their users to write declarative queries which compute recursive deductions over extensional data, leaving their high-performance operationalization (query planning, semi-naïve evaluation, and parallelization) to the engine. Such engines form the backbone of modern high-throughput applications in static analysis, security auditing, social-media mining, and business analytics. State-of-the-art engines are built upon nested …

This https://arxiv.org/abs/2401.15479 has been replaced.
link: https://scholar.google.com/scholar?q=a

Navigating the Post-API Dilemma | Search Engine Results Pages Present a Biased View of Social Media Data
Recent decisions to discontinue access to social media APIs are having detrimental effects on Internet research and the field of computational social science as a whole. This lack of access to data has been dubbed the Post-API era of Internet research. Fortunately, popular search engines have the means to crawl, capture, and surface social media data on their Search Engine Results Pages (SERP) if provided the proper search query, and may provide a solution to this dilemma. In the present work w…

This https://arxiv.org/abs/2311.02206 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csDB_…

Modern Datalog on the GPU
Modern deductive database engines (e.g., LogicBlox and Soufflé) enable their users to write declarative queries which compute recursive deductions over extensional data, leaving their high-performance operationalization (query planning, semi-naïve evaluation, and parallelization) to the engine. Such engines form the backbone of modern high-throughput applications in static analysis, security auditing, social-media mining, and business analytics. State-of-the-art engines are built upon nested …