Enhancing Query Optimization in Production: A Microsoft Journey
Explore Microsoft's innovative approach to query optimization in production environments, addressing challenges with general-purpose optimization and introducing specialized cloud-based optimizers. Learn about the implementation details, experiments conducted, and the solution proposed. Discover how
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Efficient Budget Query Process in Self-Service Banner 9.0
Accessing and navigating the Self-Service Banner 9.0 for budget queries can be simplified by following a step-by-step guide. From initiating a new finance query to selecting relevant columns and submitting the query, this process ensures accuracy and efficiency in tracking budget status by account.
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Query Optimization in Database Management Systems
This content covers the fundamentals of query optimization in Database Management Systems (DBMS), including steps involved, required information for evaluating queries, cost-based query sub-system, and the role of various components like query parser, optimizer, plan generator, and cost estimator. I
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Active Learning in Machine Learning
Active Learning (AL) is a subset of machine learning where a learning algorithm interacts with a user to label data for desired outputs. It aims to minimize the labeling bottleneck by achieving high accuracy with minimal labeled instances, thus reducing the cost of obtaining labeled data. Techniques
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Performance of Nearest Neighbor Queries in R-trees
Spatial data management research focuses on designing robust spatial data structures, inventing new models, constructing query languages, and optimizing query processing. This study explores the estimation of query performance and selectivity, specifically in R-trees, for efficient access planning.
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Shifting Bloom Filters at Peking University, China
Explore the innovative research on Shifting Bloom Filters conducted at Peking University, China, featuring evaluations, conclusions, background information, and insights on membership, association, and multiplicity queries. The study delves into hash functions, theoretical results, and the Shifting
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Advancements in Open Question Answering Over Text and Tables
Open question answering over tables and text is a challenging area in natural language processing. Various paradigms such as text-based QA, table/KB-only QA, and combined text and table QA have been explored. Incompleteness in answering specific questions like identifying the runner-up song on Billb
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Identifying Completeness of Query Answers in Incomplete Databases
The study delves into how to assess the completeness of query answers when dealing with partially complete databases. By analyzing data from a telecommunication company’s data warehouse, the query results are examined to determine if all warnings generated by maintenance objects with hardware team
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Advancements in Knowledge Graph Question Answering for Materials Science
Investigating natural language interfaces for querying structured MOF data stored in a knowledge graph, this project focuses on developing strategies using NLP to translate NL questions to KG queries. The MOF-KG integrates datasets, enabling query, computation, and reasoning for deriving new knowled
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Quantum Query Complexity Measures for Symmetric Functions
Explore the relationships between query complexity measures, including quantum query complexity, adversary bounds, and spectral sensitivity, in the context of symmetric functions. Analysis includes sensitivity graphs, the quantum query model, and approximate counting methods. Results cover spectral
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Relational Query Languages in Database Applications
In this lecture, Mohammad Hammoud discusses the importance of relational query languages (QLs) in manipulating and retrieving data in databases. He covers the strong formal foundation of QLs, their distinction from programming languages, and their effectiveness for accessing large datasets. The sess
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Introduction to Priority Search Trees in Computational Geometry
This lecture outlines the structure and query process of Priority Search Trees (PST) in computational geometry. It covers heap-based point queries, range trees for windowing queries, handling query ranges in 1D and 2D spaces, and using heaps to efficiently handle query ranges. The content discusses
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Dynamic Semantic Parser Approach for Sequential Question Answering
Using a Dynamic Semantic Parser approach, the research focuses on Sequential Question Answering (SQA) by structuring queries based on semantic parses of tables as single-table databases. The goal is to generate structured queries for questions by defining formal query languages and actions for trans
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Optimizing Join Enumeration in Transformation-based Query Optimizers
Query optimization plays a crucial role in improving database performance. This paper discusses techniques for optimizing join enumeration in transformation-based query optimizers, focusing on avoiding cross-products in join orders. It explores efficient algorithms for generating cross-product-free
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Enhancing Query-Focused Summarization with Contrastive Learning
The study explores incorporating contrastive learning into abstractive summarization systems to improve discernment between salient and non-salient content in summaries, aiming for higher relevance to the query. By designing a contrastive learning framework and utilizing segment scores, the system c
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Practical Tools for Corpus Search Using Regular Expressions and Query Languages
These notes explore practical tools for corpus search including regular expressions and the corpus query language (CQL/CQP). They provide an introduction to using corpora effectively for pattern identification, with examples and explanations. The guide includes information on levels of annotation an
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Overview of BlinkDB: Query Optimization for Very Large Data
BlinkDB is a framework built on Apache Hive, designed to support interactive SQL-like aggregate queries over massive datasets. It creates and maintains samples from data for fast, approximate query answers, supporting various aggregate functions with error bounds. The architecture includes modules f
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Study on Completeness of Queries over Incomplete Databases
Investigation into query completeness over incomplete databases, highlighting the importance of data completeness for accurate query answering. Examples and reasoning provided to illustrate the challenges and considerations in ensuring query completeness.
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Question Answering Systems in NLP: Overview and Applications
Question answering systems in natural language processing (NLP) have evolved significantly, offering solutions beyond just retrieving relevant documents. These systems cater to the fundamental human need for answers to specific questions. They excel in finding answers within document collections, da
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Real-time Question Answering Using Word Embedding and Summarization Techniques
This research project aims to improve question answering over social media platforms by leveraging word embedding and summarization methods. The approach involves retrieving a large set of candidate answers from various sources, learning to rank these answers, and summarizing the top-ranked ones. Te
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Scalable Query System for Complex Game Environments Evaluation
Designing a scalable query system for evaluating complex game environments involves key elements like defining required features, structuring query elements, and understanding function models for optimal performance. The system must be customizable, support debugging, and allow runtime parameter adj
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Jena SPARQL for Mac and RDF Queries
Jena SPARQL for Mac is a powerful tool for querying RDF graphs using SPARQL. Learn about RDF graphs, models, triples, and how SPARQL queries work. Explore ARQ, a query engine that supports the SPARQL RDF Query language and features multiple query languages. Discover how to install ARQ and execute SP
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Ensembling Diverse Approaches to Question Answering
Diverse types of question answering approaches include factoid querying, compositional querying of structured databases/knowledge graphs, reading comprehension, and visual question answering. Limitations of factoid question answering are also discussed, highlighting the need for specific queries and
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WikiQA Dataset: Open-Domain Question Answering Challenges
WikiQA Dataset provides a challenge for open-domain question answering, focusing on identifying answers from large-scale knowledge bases such as Freebase and high-quality text sources like Wikipedia. The dataset includes questions sampled from search engine query logs, with candidate sentences sourc
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Open-Domain Question Answering Dataset WikiQA Overview
This content discusses the WikiQA dataset, a challenge dataset for open-domain question answering. It covers topics such as question answering with knowledge base, answer sentence selection, QA sentence dataset, issues with QA sentence dataset, and WikiQA dataset details. Various aspects of open-dom
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BlinkDB: A Framework for Fast and Approximate Query Processing
BlinkDB is a framework built on Hive and Spark that creates and maintains offline samples for fast, approximate query processing. It provides error bars for queries executed on the same data and ensures correctness. The paper introduces innovations like sample creation techniques, error latency prof
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Unsupervised Relation Detection Using Knowledge Graphs and Query Click Logs
This study presents an approach for unsupervised relation detection by aligning query patterns extracted from knowledge graphs and query click logs. The process involves automatic alignment of query patterns to determine relations in a knowledge graph, aiding in tasks like spoken language understand
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Communication Steps for Parallel Query Processing: Insights from MPC Model
Revealing the intricacies of parallel query processing on big data, this content explores various computation models such as MapReduce, MUD, and MRC. It delves into the MPC model in detail, showcasing the tradeoffs between space exponent and computation rounds. The study uncovers lower bounds on spa
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Dichotomy on Complexity of Consistent Query Answering
The research paper presents a dichotomy on the complexity of consistent query answering for atoms with simple keys. It discusses repairs for uncertain instances in a schema with key constraints, as well as the concept of consistent query answering. The document addresses the problem statement of cer
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Automata for Query Optimization in Databases and AI
Explore the use of tree automata for reasoning, querying databases using logic languages, optimizing queries through relation algebra, and core problems in query optimization. Learn about data exchange on the web, inference of information from incomplete data, and the semantics of Datalog programs f
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Probabilistic Query Answering and Group Nearest Neighbor Queries
This chapter delves into probabilistic query types, focusing on probabilistic group nearest neighbor queries. Explore the definitions, processing techniques, and applications of such queries. Learn how probabilistic data management plays a crucial role in uncertain databases, spatial queries, and mo
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Reverse k Nearest Neighbors Query Processing: Experiments and Analysis
This study delves into the intricate process of reverse k-nearest neighbors query processing, featuring experiments and analysis by Muhammad Aamir Cheema, Xuemin Lin, Wei Wang, and Shiyu Yang. The research focuses on frameworks, algorithms like TPL++, and explores the motivations, contributions, and
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Deep Learning Project on Persian Visual Question Answering
The project "Deep Learning Course Final Project of Spring 2020" focuses on developing a solution for Persian Visual Question Answering. The project involves Alireza, Asghari, and Maryam Sadat Hashemi. This initiative explores the intersection of deep learning with the complexities of processing visu
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Query Processing in Relational Algebra: Transforming, Estimating Costs, and Generating Plans
This content delves into the intricacies of query processing at the relational algebra level. It covers transformations, estimation of costs, detailed query plan generation, and plan comparison. The process involves estimating the cost and size of query plans, calculating the number of IO operations
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Query Decomposition and Data Localization
This content discusses the process of query decomposition and data localization in databases. It covers topics such as analysis of query graphs, elimination of redundancy in queries, and rewriting queries for better efficiency. The examples provided illustrate the importance of semantic correctness
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Converting Logical Query Plans to Physical Query Plans in DBMS
Illustrations and steps involved in the process of converting logical query plans (LQP) to physical query plans (PQP) in database management systems (DBMS), focusing on optimization, algorithm implementation, and handling security issues. The images provide a visual guide to constructing physical qu
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Report Writers Meeting with Query Performance Tips
A meeting was held on 12/08/2015 with Gary Yates to discuss query performance tips for report writers. The session covered important aspects such as retrieving necessary fields, using single list views or crosstabs effectively, and keeping query calculations simple. Additionally, insights on partiti
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Approaches for Federated Query Systems and Ontology Mapping
This content delves into the methodologies, tools, and strategies involved in federated query systems, specifically focusing on ontology mapping, query construction, and types of queries within the i2b2 Star Schema. It discusses the necessity of integrating local codes into central hierarchies and p
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Enhancing Information Retrieval with Relevance Feedback & Query Expansion
In the realm of information retrieval, relevance feedback and query expansion play pivotal roles in refining search results. This lecture delves into techniques such as the Rocchio algorithm, positive vs. negative relevance feedback, and the assumptions underlying the effectiveness of relevance feed
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Efficient Query Execution on Raw Data Files
This research explores NoDB, a database system designed to eliminate the bottleneck of data-to-query time by querying raw data files in their original location. By redesigning the query processing layer to query raw data in situ state while automatically creating auxiliary structures, NoDB aims to m
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