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Top-K Entity Resolution with Adaptive Locality-Sensitive Hashing
Top-K Entity Resolution with Adaptive Locality-Sensitive Hashing Vasilis Verroios Hector Garcia-Molina Stanford University Stanford University [email protected] [email protected] ABSTRACT Given a set of records, entity resolution algorithms find all the records referring to each entity. In this paper, we study Entity 1 the problem of top-k entity resolution: finding all the records Entity 2 referring to the k largest (in terms of records) entities. Top-k Top-k Entity entity resolution is driven by many modern applications that Dataset Filtering Entities’ Records Resolution operate over just the few most popular entities in a dataset. We propose a novel approach, based on locality-sensitive hashing, that can very rapidly and accurately process mas- Entity k sive datasets. Our key insight is to adaptively decide how much processing each record requires to ascertain if it refers to a top-k entity or not: the less likely a record is to refer to Figure 1: Filtering stage in the overall workflow. a top-k entity, the less it is processed. The heavily reduced rest. As we will see, this fact makes it easier to find the top- amount of processing for the vast majority of records that k entities without computing all entities. We next illustrate do not refer to top-k entities, leads to significant speedups. two additional applications where one typically only needs Our experiments with images, web articles, and scientific top-k entities. Incidentally, two of the datasets we use for publications show a 2x to 25x speedup compared to the tra- our experiments are from these applications. -
Solving the Funarg Problem with Static Types IFL ’21, September 01–03, 2021, Online
Solving the Funarg Problem with Static Types Caleb Helbling Fırat Aksoy [email protected] fi[email protected] Purdue University Istanbul University West Lafayette, Indiana, USA Istanbul, Turkey ABSTRACT downwards. The upwards funarg problem refers to the manage- The difficulty associated with storing closures in a stack-based en- ment of the stack when a function returns another function (that vironment is known as the funarg problem. The funarg problem may potentially have a non-empty closure), whereas the down- was first identified with the development of Lisp in the 1970s and wards funarg problem refers to the management of the stack when hasn’t received much attention since then. The modern solution a function is passed to another function (that may also have a non- taken by most languages is to allocate closures on the heap, or to empty closure). apply static analysis to determine when closures can be stack allo- Solving the upwards funarg problem is considered to be much cated. This is not a problem for most computing systems as there is more difficult than the downwards funarg problem. The downwards an abundance of memory. However, embedded systems often have funarg problem is easily solved by copying the closure’s lexical limited memory resources where heap allocation may cause mem- scope (captured variables) to the top of the program’s stack. For ory fragmentation. We present a simple extension to the prenex the upwards funarg problem, an issue arises with deallocation. A fragment of System F that allows closures to be stack-allocated. returning function may capture local variables, making the size of We demonstrate a concrete implementation of this system in the the closure dynamic. -
Using the Unibasic Debugger
C:\Program Files\Adobe\FrameMaker8\UniData 7.2\7.2rebranded\DEBUGGER\BASBTITL.fm March 8, 2010 10:30 am Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta UniData Using the UniBasic Debugger UDT-720-UDEB-1 C:\Program Files\Adobe\FrameMaker8\UniData 7.2\7.2rebranded\DEBUGGER\BASBTITL.fm March 8, 2010 10:30 am Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Beta Notices Edition Publication date: July 2008 Book number: UDT-720-UDEB-1 Product version: UniData 7.2 Copyright © Rocket Software, Inc. 1988-2008. All Rights Reserved. Trademarks The following trademarks appear in this publication: Trademark Trademark Owner Rocket Software™ Rocket Software, Inc. Dynamic Connect® Rocket Software, Inc. RedBack® Rocket Software, Inc. SystemBuilder™ Rocket Software, Inc. UniData® Rocket Software, Inc. UniVerse™ Rocket Software, Inc. U2™ Rocket Software, Inc. U2.NET™ Rocket Software, Inc. U2 Web Development Environment™ Rocket Software, Inc. wIntegrate® Rocket Software, Inc. Microsoft® .NET Microsoft Corporation Microsoft® Office Excel®, Outlook®, Word Microsoft Corporation Windows® Microsoft Corporation Windows® 7 Microsoft Corporation Windows Vista® Microsoft Corporation Java™ and all Java-based trademarks and logos Sun Microsystems, Inc. UNIX® X/Open Company Limited ii Using the UniBasic Debugger The above trademarks are property of the specified companies in the United States, other countries, or both. All other products or services mentioned in this document may be covered by the trademarks, service marks, or product names as designated by the companies who own or market them. License agreement This software and the associated documentation are proprietary and confidential to Rocket Software, Inc., are furnished under license, and may be used and copied only in accordance with the terms of such license and with the inclusion of the copyright notice. -
Kednos PL/I for Openvms Systems User Manual
) Kednos PL/I for OpenVMS Systems User Manual Order Number: AA-H951E-TM November 2003 This manual provides an overview of the PL/I programming language. It explains programming with Kednos PL/I on OpenVMS VAX Systems and OpenVMS Alpha Systems. It also describes the operation of the Kednos PL/I compilers and the features of the operating systems that are important to the PL/I programmer. Revision/Update Information: This revised manual supersedes the PL/I User’s Manual for VAX VMS, Order Number AA-H951D-TL. Operating System and Version: For Kednos PL/I for OpenVMS VAX: OpenVMS VAX Version 5.5 or higher For Kednos PL/I for OpenVMS Alpha: OpenVMS Alpha Version 6.2 or higher Software Version: Kednos PL/I Version 3.8 for OpenVMS VAX Kednos PL/I Version 4.4 for OpenVMS Alpha Published by: Kednos Corporation, Pebble Beach, CA, www.Kednos.com First Printing, August 1980 Revised, November 1983 Updated, April 1985 Revised, April 1987 Revised, January 1992 Revised, May 1992 Revised, November 1993 Revised, April 1995 Revised, October 1995 Revised, November 2003 Kednos Corporation makes no representations that the use of its products in the manner described in this publication will not infringe on existing or future patent rights, nor do the descriptions contained in this publication imply the granting of licenses to make, use, or sell equipment or software in accordance with the description. Possession, use, or copying of the software described in this publication is authorized only pursuant to a valid written license from Kednos Corporation or an anthorized sublicensor. -
Data General Extended Algol 60 Compiler
DATA GENERAL EXTENDED ALGOL 60 COMPILER, Data General's Extended ALGOL is a powerful language tial I/O with optional formatting. These extensions comple which allows systems programmers to develop programs ment the basic structure of ALGOL and significantly in on mini computers that would otherwise require the use of crease the convenience of ALGOL programming without much larger, more expensive computers. No other mini making the language unwieldy. computer offers a language with the programming features and general applicability of Data General's Extended FEATURES OF DATA GENERAL'S EXTENDED ALGOL Character strings are implemented as an extended data ALGOL. type to allow easy manipulation of character data. The ALGOL 60 is the most widely used language for describ program may, for example, read in character strings, search ing programming algorithms. It has a flexible, generalized, for substrings, replace characters, and maintain character arithmetic organization and a modular, "building block" string tables efficiently. structure that provides clear, easily readable documentation. Multi-precision arithmetic allows up to 60 decimal digits The language is powerful and concise, allowing the systems of precision in integer or floating point calculations. programmer to state algorithms without resorting to "tricks" Device-independent I/O provides for reading and writ to bypass the language. ing in line mode, sequential mode, or random mode.' Free These characteristics of ALGOL are especially important form reading and writing is permitted for all data types, or in the development of working prototype systems. The output can be formatted according to a "picture" of the clear documentation makes it easy for the programmer to output line or lines. -
Java: Exercises in Style
Java: Exercises in Style Marco Faella June 1, 2018 i ii This work is licensed under the Creative Commons Attribution- NonCommercial 4.0 International License. To view a copy of this li- cense, visit http://creativecommons.org/licenses/by-nc/4.0/ or send a letter to Creative Commons, PO Box 1866, Mountain View, CA 94042, USA. Author: Marco Faella, [email protected] Preface to the Online Draft This draft is a partial preview of what may eventually become a book. The idea is to share it with the public and obtain feedback to improve its quality. So, if you read the whole draft, or maybe just a chapter, or you just glance over it long enough to spot a typo, let me know! I’m interested in all comments and suggestions for improvement, including (natural) language issues, programming, book structure, etc. I would like to thank all the students who have attended my Programming Languages class, during the past 11 years. They taught me that there is no limit to the number of ways you may think to have solved a Java assignment. Naples, Italy Marco Faella January 2018 iii Contents Contents iv I Preliminaries 1 1 Introduction 3 1.1 Software Qualities . 5 2 Problem Statement 9 2.1 Data Model and Representations . 10 3 Hello World! 13 4 Reference Implementation 17 4.1 Space Complexity . 21 4.2 Time Complexity . 23 II Software Qualities 29 5 Need for Speed 31 5.1 Optimizing “getAmount” and “addWater” . 32 5.2 Optimizing “connectTo” and “addWater” . 34 5.3 The Best Balance: Union-Find Algorithms . -
Supplementary Materials
Contents 2 Programming Language Syntax C 1 2.3.5 Syntax Errors C 1 2.4 Theoretical Foundations C 13 2.4.1 Finite Automata C 13 2.4.2 Push-Down Automata C 18 2.4.3 Grammar and Language Classes C 19 2.6 Exercises C 24 2.7 Explorations C 25 3 Names, Scopes, and Bindings C 26 3.4 Implementing Scope C 26 3.4.1 Symbol Tables C 26 3.4.2 Association Lists and Central Reference Tables C 31 3.8 Separate Compilation C 36 3.8.1 Separate Compilation in C C 37 3.8.2 Packages and Automatic Header Inference C 40 3.8.3 Module Hierarchies C 41 3.10 Exercises C 42 3.11 Explorations C 44 4SemanticAnalysis C 45 4.5 Space Management for Attributes C 45 4.5.1 Bottom-Up Evaluation C 45 4.5.2 Top-Down Evaluation C 50 C ii Contents 4.8 Exercises C 57 4.9 Explorations C 59 5 Target Machine Architecture C 60 5.1 The Memory Hierarchy C 61 5.2 Data Representation C 63 5.2.1 Integer Arithmetic C 65 5.2.2 Floating-Point Arithmetic C 67 5.3 Instruction Set Architecture (ISA) C 70 5.3.1 Addressing Modes C 71 5.3.2 Conditions and Branches C 72 5.4 Architecture and Implementation C 75 5.4.1 Microprogramming C 76 5.4.2 Microprocessors C 77 5.4.3 RISC C 77 5.4.4 Multithreading and Multicore C 78 5.4.5 Two Example Architectures: The x86 and ARM C 80 5.5 Compiling for Modern Processors C 88 5.5.1 Keeping the Pipeline Full C 89 5.5.2 Register Allocation C 93 5.6 Summary and Concluding Remarks C 98 5.7 Exercises C 100 5.8 Explorations C 104 5.9 Bibliographic Notes C 105 6 Control Flow C 107 6.5.4 Generators in Icon C 107 6.7 Nondeterminacy C 110 6.9 Exercises C 116 6.10 Explorations -
CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 12
CS412/CS413 Introduction to Compilers Tim Teitelbaum Lecture 12: Symbol Tables February 15, 2008 CS 412/413 Spring 2008 Introduction to Compilers 1 Where We Are Source code if (b == 0) a = b; (character stream) Lexical Analysis Token if ( b == 0 ) a = b ; stream Syntax Analysis if (Parsing) == = Abstract syntax tree (AST) b0ab if Semantic Analysis boolean int Decorated == = AST int b int 0 int a int b Errors lvalue (incorrect program) CS 412/413 Spring 2008 Introduction to Compilers 2 Non-Context-Free Syntax • Programs that are correct with respect to the language’s lexical and context-free syntactic rules may still contain other syntactic errors • Lexical analysis and context-free syntax analysis are not powerful enough to ensure the correct usage of variables, objects, functions, statements, etc. • Non-context-free syntactic analysis is known as semantic analysis CS 412/413 Spring 2008 Introduction to Compilers 3 Incorrect Programs •Example 1: lexical analysis does not distinguish between different variable or function identifiers (it returns the same token for all identifiers) int a; int a; a = 1; b = 1; •Example 2: syntax analysis does not correlate the declarations with the uses of variables in the program: int a; a = 1; a = 1; •Example3: syntax analysis does not correlate the types from the declarations with the uses of variables: int a; int a; a = 1; a = 1.0; CS 412/413 Spring 2008 Introduction to Compilers 4 Goals of Semantic Analysis • Semantic analysis ensures that the program satisfies a set of additional rules regarding the -
Graph Reduction Without Pointers
Graph Reduction Without Pointers TR89-045 December, 1989 William Daniel Partain The University of North Carolina at Chapel Hill Department of Computer Science ! I CB#3175, Sitterson Hall Chapel Hill, NC 27599-3175 UNC is an Equal Opportunity/Aflirmative Action Institution. Graph Reduction Without Pointers by William Daniel Partain A dissertation submitted to the faculty of the University of North Carolina at Chapel Hill in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Computer Science. Chapel Hill, 1989 Approved by: Jfn F. Prins, reader ~ ~<---( CJ)~ ~ ;=tfJ\ Donald F. Stanat, reader @1989 William D. Partain ALL RIGHTS RESERVED II WILLIAM DANIEL PARTAIN. Graph Reduction Without Pointers (Under the direction of Gyula A. Mag6.) Abstract Graph reduction is one way to overcome the exponential space blow-ups that simple normal-order evaluation of the lambda-calculus is likely to suf fer. The lambda-calculus underlies lazy functional programming languages, which offer hope for improved programmer productivity based on stronger mathematical underpinnings. Because functional languages seem well-suited to highly-parallel machine implementations, graph reduction is often chosen as the basis for these machines' designs. Inherent to graph reduction is a commonly-accessible store holding nodes referenced through "pointers," unique global identifiers; graph operations cannot guarantee that nodes directly connected in the graph will be in nearby store locations. This absence of locality is inimical to parallel computers, which prefer isolated pieces of hardware working on self-contained parts of a program. In this dissertation, I develop an alternate reduction system using "sus pensions" (delayed substitutions), with terms represented as trees and vari ables by their binding indices (de Bruijn numbers). -
Design and Implementation of the GNU Prolog System Abstract 1 Introduction
Design and Implementation of the GNU Prolog System Daniel Diaz Philippe Codognet University of Paris 1 University of Paris 6 CRI, bureau C1407 LIP6, case 169 90, rue de Tolbiac 8, rue du Capitaine Scott 75013 Paris, FRANCE 75015 Paris, FRANCE and INRIA-Rocquencourt and INRIA-Rocquencourt [email protected] [email protected] Abstract In this paper we describe the design and the implementation of the GNU Pro- log system. This system draws on our previous experience of compiling Prolog to C in the wamcc system and of compiling finite domain constraints in the clp(FD) system. The compilation scheme has however been redesigned in or- der to overcome the drawbacks of compiling to C. In particular, GNU-Prolog is based on a low-level mini-assembly platform-independent language that makes it possible to avoid compiling C code, and thus drastically reduces compilation time. It also makes it possible to produce small stand-alone executable files as the result of the compilation process. Interestingly, GNU Prolog is now com- pliant to the ISO standard, includes several extensions (OS interface, sockets, global variables, etc) and integrates a powerful constraint solver over finite domains. The system is efficient and in terms of performance is comparable with commercial systems for both the Prolog and constraint aspects. 1 Introduction GNU Prolog is a free Prolog compiler supported by the GNU organization (http://www.gnu.org/software/prolog). It is a complete system which in- cludes: floating point numbers, streams, dynamic code, DCG, operating sys- tem interface, sockets, a Prolog debugger, a low-level WAM debugger, line editing facilities with completion on atoms, etc. -
Interpreters Machine Interpreters
Interpreters There are two different kinds of interpreters that support execution of programs, machine interpreters and language interpreters. Machine Interpreters A machine interpreter simulates the execution of a program compiled for a particular machine architecture. Java uses a bytecode interpreter to simulate the effects of programs compiled for the JVM. Programs like SPIM simulate the execution of a MIPS program on a non-MIPS computer. © CS 536 Spring 2006 43 Language Interpreters A language interpreter simulates the effect of executing a program without compiling it to any particular instruction set (real or virtual). Instead some IR form (perhaps an AST) is used to drive execution. Interpreters provide a number of capabilities not found in compilers: • Programs may be modified as execution proceeds. This provides a straightforward interactive debugging capability. Depending on program structure, program modifications may require reparsing or repeated semantic analysis. In Python, for example, any string variable may be interpreted as a Python expression or statement and executed. © CS 536 Spring 2006 44 • Interpreters readily support languages in which the type of a variable denotes may change dynamically (e.g., Python or Scheme). The user program is continuously reexamined as execution proceeds, so symbols need not have a fixed type. Fluid bindings are much more troublesome for compilers, since dynamic changes in the type of a symbol make direct translation into machine code difficult or impossible. • Interpreters provide better diagnostics. Source text analysis is intermixed with program execution, so especially good diagnostics are available, along with interactive debugging. • Interpreters support machine independence. All operations are performed within the interpreter. -
Design and Implementation of the Symbol Table for Object- Oriented Programming Language
International Journal of Database Theory and Application Vol.10, No.7 (2017), pp.27-40 http://dx.doi.org/10.14257/ijdta.2017.10.7.03 Design and Implementation of the Symbol Table for Object- Oriented Programming Language Yangsun Lee Dept. of of Computer Engineering, Seokyeong University 16-1 Jungneung-Dong, Sungbuk-Ku, Seoul 136-704, KOREA [email protected] Abstract The symbol table used in the existing compiler stores one symbol information into a plurality of sub tables, and the abstract syntax tree necessary for generating symbols has a binary tree structure composed of a single data structure node. This structure increases the source code complexity of modules that generate symbols and modules that reference symbol tables, and when designing a compiler for a new language, it is necessary to newly design an abstract syntax tree and a symbol table structure considering the characteristics of the language. In this paper, we apply the object-oriented principle and visitor pattern to improve the abstract syntax tree structure and design and implement the symbol table for the object - oriented language. The design of AST (abstract syntax trees) with object-oriented principles and Visitor patterns reduces the time and cost of redesign because it makes it easy to add features of the language without the need to redesign the AST (abstract syntax tree) for the new object-oriented language. In addition, it is easy to create a symbol through the Visitor pattern. Symbol tables using the open-close principle and the dependency inversion principle can improve the code reusability of the source code that creates and refer to the table and improve the readability of the code.