DOCSLIB.ORG

Directions in AI Research and Applications at Siemens Corporate

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Directions in AI Research and Applications at Siemens Corporate AI Magazine Volume 11 Number 1 (1991)(1990) (© AAAI) Research in Progress of linguistic phenomena. The com- Directions in AI Research putational work concerns questions of adequate processing models and algorithms, as embodied in the and Applications at actual interfaces being developed. These topics are explored in the Siemens Corporate Research framework of three projects: The nat- ural language consulting dialogue and Development project (Wisber) takes up research- oriented topics (descriptive grammar formalisms and linguistically adequate grammar specification, handling of Wolfram Buettner, Klaus Estenfeld, discourse, and so on), the data-access Hans Haugeneder, and Peter Struss project (Sepp) focuses on the practi- cal application of state-of-the-art technology, and the work on gram- mar-development environments ■ Many barriers exist today that prevent particular, Prolog extensions; and (4) (Ape) centers on the problem of ade- effective industrial exploitation of current design and analysis of neural networks. quate tools for specifying linguistic and future AI research. These barriers can The lab’s 26 researchers are orga- knowledge sources and efficient pro- only be removed by people who are work- nized into four groups corresponding cessing methods. ing at the scientific forefront in AI and to these areas. Together, they provide Wisber is jointly funded by the know potential industrial needs. Siemens with innovative software The Knowledge Processing Laboratory’s German government and several research and development concentrates in technologies, appropriate applications, industrial and academic partners. the following areas: (1) natural language prototypical implementations of AI The goal of the project is to develop interfaces to knowledge-based systems and systems, and evaluations of new a knowledge-based advice-giving databases; (2) theoretical and experimen- techniques and trends. system in the domain of financial tal work on qualitative modeling and In addition to its responsibilities to consultation. nonmonotonic reasoning for future knowl- the company, the lab aims at estab- edge-based systems; (3) application-specif- lishing close contacts with the out- The group's ic language design, in particular, Prolog side scientific community. In part, extensions; and (4) design and analysis of this contact is made by sharing tech- general strategy neural networks. nical results and advances in AI This article gives the reader an overview for validating its of the main topics currently being pursued technology and its theoretical foun- theoretical work is in each of these areas. dations. Furthermore, lab researchers support a two-way exchange of infor- to build prototypi- mation through publications and Many barriers exist today that pre- talks on current work as well as activ- cal tools and vent effective industrial exploitation ities as referees, teachers at tutorials, integrate them of current and future AI research. and conference organizers. into a system. These barriers can only be removed The remainder of this article gives by people who are working at the the reader an overview of the main scientific forefront in AI and know topics currently being pursued in The natural language analysis com- potential industrial needs. each of the four groups. ponent is the laboratory’s responsi- The Knowledge Processing Lab- bility. It is based on a lexical-func- oratory within Siemens Corporate Natural Language tional grammar (LFG)–type parser Research and Development in Technology (Block and Hunze 1986; Block and Munich, Germany, aims at breaking Haugeneder 1988) but handles long- down these barriers. With over Current state-of-the-art natural lan- distance phenomena more in the 350,000 employees and a product guage interfaces have many limita- spirit of the slash categories of the line ranging from coffee makers to tions. Among these are a linguistic generalized phrase structure gram- mainframe computers, Siemens is coverage that is too narrow, restricted mar. It uses discourse representation one of the world’s leading high-tech types of dialogue interaction, insuffi- theory (DRT) as the framework for its companies. Its interest in leading- cient robustness, and modeling of semantic and discourse representa- edge technologies such as AI is the application domain that is too tion (Hunze 1988; Frederking and understandable. implicit. Gehrke 1988). A KL-TWO–type repre- The Knowledge Processing Labora- To develop interfaces that do not sentation formalism is used for con- tory’s research and development con- exhibit these limitations, the Natural ceptual modeling. A grammar centrates in the following areas: (1) Language Technology Group is compiler developed by the laboratory natural language interfaces to knowl- engaged in basic research and in the allows grammars to be perspicuously edge-based systems and databases; (2) development of actual applications. written but efficiently processed. theoretical and experimental work The theoretical work encompasses Because morphology is of critical on qualitative modeling and non- such elements as the development of importance in German, we also monotonic reasoning for future expressive formal representations for developed a morphological analyzer knowledge-based systems; (3) appli- linguistic knowledge and empirically using the same formalism as for syn- cation-specific language design, in tested, formally explicit descriptions tactic analysis. Additionally, we 20 AI MAGAZINE Copyright ©1990 AAAI. All rights reserved. 0738-4602/89/$4.00 Research in Progress implemented a component for han- facilities. The next version of this control strategies (Haugeneder and dling and accessing large lexicons on interface will employ left-corner Gehrke 1987) using an agenda con- the basis of discrimination trees and parsing, making use of bottom-up trol mechanism. These capabilities random-access methods (Gehrke and information in addition to the top- have been used extensively in the Block 1986). A sizable, restrictively down information already used. development of heuristic search formulated German grammar is Work also continues on extending strategies that are independent of the being developed as part of this work Sepp’s linguistic coverage, especially underlying grammar formalism (Hau- using government and binding con- with regard to quantifiers, ellipses, geneder and Gehrke 1988). Ape is cepts within an LFG representation and comparative constructions (the implemented in Interlisp-D on a (Schachtl 1988). These components latter are currently handled by semi- Siemens 58xx. run in Interlisp-D on a Siemens 58xx formal expressive features). Enlarging To provide a focus for future work, (Xerox 1100) workstation. the functionality and user friendli- we have adopted the ambitious goal Sepp (SESAM preprocessor) is a ness of Sepp’s domain-tailoring tools of developing a linguistic core pro- natural language interface to database will also be tackled (Schmid 1988). cessor (LCP) that will bring together systems supporting the standard The development of the system is the results of the work in the three query language SQL (Block and being performed in Prolog on SUN preceding projects. LCP will be an Schlereth 1987). Included are tools workstations, with Siemens MX integrated, application-neutral natu- for adjusting the domain-indepen- (Unix-based) computers as target ral language–processing component dent language processor to a specific machines. having linguistic capabilities ade- database. Sepp functions as a transla- The Ape (augmented transition quate for a variety of interface uses. tor, producing SQL queries in a two- network [ATN] programming envi- LCP is envisioned not only as being phase process. Natural language ronment) grammar-development parameterized with respect to domain queries are mapped into SQL queries environment is a highly interactive but also as being usable as a natural through an intermediate abstract, development and testing environ- language interaction component in object-centered internal representation. ment for the ATN formalism based multimodal user interfaces. The natu- The current version of Sepp is being on an active chart parser (Haugened- ral language facilities of LCP will used in a pilot project by an organi- er and Gehrke 1986). This system include the analysis of natural lan- zation outside Siemens to access allows the specification and debug- guage input as well as the generation information in its large, real-world ging of network-style grammars of natural language output. In its database. This experience will give us using an extensive graphic interface final version, it will have comprehen- feedback on the system’s language and provides a highly flexible tool sive coverage and be robust in the coverage, habitability, and overall for defining and testing various face of ungrammatical input, attentive SPRING 1990 21 Research in Progress to its discourse context, and alert to As implemented, this framework the implications of a variety of speech The statement of deals with hierarchical models and acts. Of course, the initial version a problem should allows focusing within these models will be significantly limited compared at the same time (Struss 1988a, 1988b), handles to the eventual LCP, with develop- dynamic device models (Dressler and ment proceeding incrementally. be an executable Freitag 1989), and integrates fault Participants: H. Haugeneder, H. U. computer program models exploiting the extended Block, R. Frederking (until June 1989), ATMS (Struss
Load more

Recommended publications
  • Realising the Potential of Algal Biomass Production Through Semantic Web and Linked Data
    LEAPS: Realising the Potential of Algal Biomass Production through Semantic Web and Linked data ∗ Monika Solanki Johannes Skarka Craig Chapman KBE Lab Karlsruhe Institute of KBE Lab Birmingham City University Technology (ITAS) Birmingham City University [email protected] [email protected] [email protected] ABSTRACT In order to derive fuels from biomass, algal operation plant Recently algal biomass has been identified as a potential sites are setup that facilitate biomass cultivation and con- source of large scale production of biofuels. Governments, version of the biomass into end use products, some of which environmental research councils and special interests groups are biofuels. Microalgal biomass production in Europe is are funding several efforts that investigate renewable energy seen as a promising option for biofuels production regarding production opportunities in this sector. However so far there energy security and sustainability. Since microalgae can be has been no systematic study that analyses algal biomass cultivated in photobioreactors on non-arable land this tech- potential especially in North-Western Europe. In this paper nology could significantly reduce the food vs. fuel dilemma. we present a spatial data integration and analysis frame- However, until now there has been no systematic analysis work whereby rich datasets from the algal biomass domain of the algae biomass potential for North-Western Europe. that include data about algal operation sites and CO2 source In [20], the authors assessed the resource potential for mi- sites amongst others are semantically enriched with ontolo- croalgal biomass but excluded all areas not between 37◦N gies specifically designed for the domain and made available and 37◦S, thus most of Europe.
    [Show full text]
  • From Cataloguing Cards to Semantic Web 1
    View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Scientific Open-access Literature Archive and Repository Archeologia e Calcolatori 20, 2009, 111-128 REPRESENTING KNOWLEDGE IN ARCHAEOLOGY: FROM CATALOGUING CARDS TO SEMANTIC WEB 1. Introduction Representing knowledge is the basis of any catalogue. The Italian Ca- talogue was based on very valuable ideas, developed in the late 1880s, with the basic concept of putting objects in their context. Initially cataloguing was done manually, with typewritten cards. The advent of computers led to some early experimentations, and subsequently to the de�nition of a more formalized representation schema. The web produced a cultural revolution, and made the need for technological and semantic interoperability more evi- dent. The Semantic Web scenario promises to allow a sharing of knowledge, which will make the knowledge that remained unexpressed in the traditional environments available to any user, and allow objects to be placed in their cultural context. In this paper we will brie�y recall the principles of cataloguing and lessons learned by early computer experiences. Subsequently we will descri- be the object model for archaeological items, discussing its strong and weak points. In section 5 we present the web scenario and approaches to represent knowledge. 2. Cataloguing: history and principles The Italian Catalogue of cultural heritage has its roots in the experiences and concepts, developed in the late 1880s and early 1900s, by the famous art historian Adolfo Venturi, who was probably one of the �rst scholars to think explicitly in terms of having a frame of reference to describe works of art, emphasizing as the main issue the context in which the work had been produced.
    [Show full text]
  • Download Slides
    a platform for all that we know savas parastatidis http://savas.me savasp transition from web to apps increasing focus on information (& knowledge) rise of personal digital assistants importance of near-real time processing http://aptito.com/blog/wp-content/uploads/2012/05/smartphone-apps.jpg today... storing computing computers are huge amounts great tools for of data managing indexing example google and microsoft both have copies of the entire web (and more) for indexing purposes tomorrow... storing computing computers are huge amounts great tools for of data managing indexing acquisition discovery aggregation organization we would like computers to of the world’s information also help with the automatic correlation analysis and knowledge interpretation inference data information knowledge intelligence wisdom expert systems watson freebase wolframalpha rdbms google now web indexing data is symbols (bits, numbers, characters) information adds meaning to data through the introduction of relationship - it answers questions such as “who”, “what”, “where”, and “when” knowledge is a description of how the world works - it’s the application of data and information in order to answer “how” questions G. Bellinger, D. Castro, and A. Mills, “Data, Information, Knowledge, and Wisdom,” Inform. pp. 1–4, 2004 web – the data platform web – the information platform web – the knowledge platform foundation for new experiences “wisdom is not a product of schooling but of the lifelong attempt to acquire it” representative examples wolframalpha watson source:
    [Show full text]
  • Knowledge Extraction for Hybrid Question Answering
    KNOWLEDGEEXTRACTIONFORHYBRID QUESTIONANSWERING Von der Fakultät für Mathematik und Informatik der Universität Leipzig angenommene DISSERTATION zur Erlangung des akademischen Grades Doctor rerum naturalium (Dr. rer. nat.) im Fachgebiet Informatik vorgelegt von Ricardo Usbeck, M.Sc. geboren am 01.04.1988 in Halle (Saale), Deutschland Die Annahme der Dissertation wurde empfohlen von: 1. Professor Dr. Klaus-Peter Fähnrich (Leipzig) 2. Professor Dr. Philipp Cimiano (Bielefeld) Die Verleihung des akademischen Grades erfolgt mit Bestehen der Verteidigung am 17. Mai 2017 mit dem Gesamtprädikat magna cum laude. Leipzig, den 17. Mai 2017 bibliographic data title: Knowledge Extraction for Hybrid Question Answering author: Ricardo Usbeck statistical information: 10 chapters, 169 pages, 28 figures, 32 tables, 8 listings, 5 algorithms, 178 literature references, 1 appendix part supervisors: Prof. Dr.-Ing. habil. Klaus-Peter Fähnrich Dr. Axel-Cyrille Ngonga Ngomo institution: Leipzig University, Faculty for Mathematics and Computer Science time frame: January 2013 - March 2016 ABSTRACT Over the last decades, several billion Web pages have been made available on the Web. The growing amount of Web data provides the world’s largest collection of knowledge.1 Most of this full-text data like blogs, news or encyclopaedic informa- tion is textual in nature. However, the increasing amount of structured respectively semantic data2 available on the Web fosters new search paradigms. These novel paradigms ease the development of natural language interfaces which enable end- users to easily access and benefit from large amounts of data without the need to understand the underlying structures or algorithms. Building a natural language Question Answering (QA) system over heteroge- neous, Web-based knowledge sources requires various building blocks.
    [Show full text]
  • Datatone: Managing Ambiguity in Natural Language Interfaces for Data Visualization Tong Gao1, Mira Dontcheva2, Eytan Adar1, Zhicheng Liu2, Karrie Karahalios3
    DataTone: Managing Ambiguity in Natural Language Interfaces for Data Visualization Tong Gao1, Mira Dontcheva2, Eytan Adar1, Zhicheng Liu2, Karrie Karahalios3 1University of Michigan, 2Adobe Research 3University of Illinois, Ann Arbor, MI San Francisco, CA Urbana Champaign, IL fgaotong,[email protected] fmirad,[email protected] [email protected] ABSTRACT to be both flexible and easy to use. General purpose spread- Answering questions with data is a difficult and time- sheet tools, such as Microsoft Excel, focus largely on offer- consuming process. Visual dashboards and templates make ing rich data transformation operations. Visualizations are it easy to get started, but asking more sophisticated questions merely output to the calculations in the spreadsheet. Asking often requires learning a tool designed for expert analysts. a “visual question” requires users to translate their questions Natural language interaction allows users to ask questions di- into operations on the spreadsheet rather than operations on rectly in complex programs without having to learn how to the visualization. In contrast, visual analysis tools, such as use an interface. However, natural language is often ambigu- Tableau,1 creates visualizations automatically based on vari- ous. In this work we propose a mixed-initiative approach to ables of interest, allowing users to ask questions interactively managing ambiguity in natural language interfaces for data through the visualizations. However, because these tools are visualization. We model ambiguity throughout the process of often intended for domain specialists, they have complex in- turning a natural language query into a visualization and use terfaces and a steep learning curve. algorithmic disambiguation coupled with interactive ambigu- Natural language interaction offers a compelling complement ity widgets.
    [Show full text]
  • A Framework for Ontology-Based Library Data Generation, Access and Exploitation
    Universidad Politécnica de Madrid Departamento de Inteligencia Artificial DOCTORADO EN INTELIGENCIA ARTIFICIAL A framework for ontology-based library data generation, access and exploitation Doctoral Dissertation of: Daniel Vila-Suero Advisors: Prof. Asunción Gómez-Pérez Dr. Jorge Gracia 2 i To Adelina, Gustavo, Pablo and Amélie Madrid, July 2016 ii Abstract Historically, libraries have been responsible for storing, preserving, cata- loguing and making available to the public large collections of information re- sources. In order to classify and organize these collections, the library commu- nity has developed several standards for the production, storage and communica- tion of data describing different aspects of library knowledge assets. However, as we will argue in this thesis, most of the current practices and standards available are limited in their ability to integrate library data within the largest information network ever created: the World Wide Web (WWW). This thesis aims at providing theoretical foundations and technical solutions to tackle some of the challenges in bridging the gap between these two areas: library science and technologies, and the Web of Data. The investigation of these aspects has been tackled with a combination of theoretical, technological and empirical approaches. Moreover, the research presented in this thesis has been largely applied and deployed to sustain a large online data service of the National Library of Spain: datos.bne.es. Specifically, this thesis proposes and eval- uates several constructs, languages, models and methods with the objective of transforming and publishing library catalogue data using semantic technologies and ontologies. In this thesis, we introduce marimba-framework, an ontology- based library data framework, that encompasses these constructs, languages, mod- els and methods.
    [Show full text]
  • Ontologies to Interpret Remote Sensing Images: Why Do We Need Them?
    Ontologies to interpret remote sensing images : why do we need them? Damien Arvor, Mariana Belgiu, Zoe Falomir, Isabelle Mougenot, Laurent Durieux To cite this version: Damien Arvor, Mariana Belgiu, Zoe Falomir, Isabelle Mougenot, Laurent Durieux. Ontologies to inter- pret remote sensing images : why do we need them?. GIScience and Remote Sensing, Taylor & Francis: STM, Behavioural Science and Public Health Titles, 2019, pp.1-29. 10.1080/15481603.2019.1587890. halshs-02079438 HAL Id: halshs-02079438 https://halshs.archives-ouvertes.fr/halshs-02079438 Submitted on 26 Mar 2019 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. GIScience & Remote Sensing ISSN: 1548-1603 (Print) 1943-7226 (Online) Journal homepage: https://www.tandfonline.com/loi/tgrs20 Ontologies to interpret remote sensing images: why do we need them? Damien Arvor, Mariana Belgiu, Zoe Falomir, Isabelle Mougenot & Laurent Durieux To cite this article: Damien Arvor, Mariana Belgiu, Zoe Falomir, Isabelle Mougenot & Laurent Durieux (2019): Ontologies to interpret remote sensing images: why do we need them?, GIScience & Remote Sensing To link to this article: https://doi.org/10.1080/15481603.2019.1587890 © 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
    [Show full text]
  • Question Answering
    Question Answering What is Ques+on Answering? Dan Jurafsky Ques%on Answering One of the oldest NLP tasks (punched card systems in 1961) Simmons, Klein, McConlogue. 1964. Indexing and ( ( Dependency Logic for Answering English Quesons. !"#$%&' )&*#'%+,-.'$/#0$ American Documentaon 15:30, 196-204 What do worms eat? Worms eat grass Horses with worms eat grass worms horses worms eat with eat eat grass worms grass what Birds eat worms Grass is eaten by worms birds worms eat eat 2 worms grass Dan Jurafsky Ques%on Answering: IBM’s Watson • Won Jeopardy on February 16, 2011! WILLIAM WILKINSON’S “AN ACCOUNT OF THE PRINCIPALITIES OF WALLACHIA AND MOLDOVIA” Bram Stoker INSPIRED THIS AUTHOR’S MOST FAMOUS NOVEL 3 Dan Jurafsky Apple’s Siri 4 Dan Jurafsky Wolfram Alpha 5 Dan Jurafsky Types of Ques%ons in Modern Systems • Factoid ques+ons • Who wrote “The Universal Declara4on of Human Rights”? • How many calories are there in two slices of apple pie? • What is the average age of the onset of au4sm? • Where is Apple Computer based? • Complex (narrave) ques+ons: • In children with an acute febrile illness, what is the efficacy of acetaminophen in reducing fever? • What do scholars think about Jefferson’s posi4on on dealing with pirates? 6 Dan Jurafsky Commercial systems: mainly factoid quesons Where is the Louvre Museum located? In Paris, France What’s the abbreviaon for limited L.P. partnership? What are the names of Odin’s ravens? Huginn and Muninn What currency is used in China? The yuan What kind of nuts are used in marzipan? almonds What instrument does
    [Show full text]
  • Ques+On Answering
    Queson Answering Debapriyo Majumdar Information Retrieval – Spring 2015 Indian Statistical Institute Kolkata Adapted from slides by Dan Jurafsky (Stanford) and Tao Yang (UCSB) Queson Answering One of the oldest NLP tasks (punched card systems in 1961) Simmons, Klein, McConlogue. 1964. Indexing and Dependency Logic for Answering English Ques%on: Poten%al-Answers: Questions. American Documentation 15:30, 196-204 What do worms eat? Worms eat grass Horses with worms eat grass worms horses worms eat with eat eat grass worms grass what Birds eat worms Grass is eaten by worms birds worms eat eat worms grass 2 Ques%on Answering: IBM’s Watson § Won Jeopardy on February 16, 2011! WILLIAM WILKINSON’S “AN ACCOUNT OF THE PRINCIPALITIES OF WALLACHIA AND MOLDOVIA” Bram Stoker INSPIRED THIS AUTHOR’S MOST FAMOUS NOVEL 3 Apple’s Siri § A seemingly “limited” set of few possible questions § Answers based on contextual parameters 4 Wolfram Alpha, Google 5 Wolfram Alpha But in this case, Google returns a standard list of document links 6 Types of Ques%ons in Modern Systems § Factoid questions – Answers are short – The question can be rephrased as “fill in the blanks” question Examples: – Who directed the movie Titanic? – How many calories are there in two slices of apple pie? – Where is Louvre museum located? § Complex (narrative) questions: – What precautionary measures should we take to be safe from swine flu? – What do scholars think about Jefferson’s position on dealing with pirates? 7 Paradigms for QA § IR-based approaches – TREC QA Track (AskMSR, ISI,
    [Show full text]
  • The Negative Impact of A-Box Materialization on Rdf2vec Knowledge Graph Embeddings
    More is not Always Better: The Negative Impact of A-box Materialization on RDF2vec Knowledge Graph Embeddings Andreea Ianaa, Heiko Paulheima aData and Web Science Group, University of Mannheim, Germany Abstract RDF2vec is an embedding technique for representing knowledge graph entities in a continuous vector space. In this paper, we investigate the effect of materializing implicit A-box axioms induced by subproperties, as well as symmetric and transitive properties. While it might be a reasonable assumption that such a materialization before computing embeddings might lead to better embeddings, we conduct a set of experiments on DBpedia which demonstrate that the materialization actually has a negative effect on the performance of RDF2vec. In our analysis, we argue that despite the huge body of work devotedon completing missing information in knowledge graphs, such missing implicit information is actually a signal, not a defect, and we show examples illustrating that assumption. Keywords RDF2Vec, Embedding, Reasoning, Knowledge Graph Completion, A-box Materialization 1. Introduction A straightforward assumption is that completing miss- ing knowledge in a knowledge graph before computing RDFvec [1] was originally conceived for exploiting knowl- node representations will lead to better results. However, edge graphs in data mining. Since most popular data in this paper, we show that the opposite actually holds: mining tools require a feature vector representation of completing the knowledge graph before computing an records, various techniques have been proposed for cre- RDF2vec embedding actually leads to worse results in ating vector space representations from subgraphs, in- downstream tasks. cluding adding datatype properties as features or creat- ing binary features for types [2].
    [Show full text]
  • Question Answering
    Queson Answering Evangelos Kanoulas [email protected] Question answering EVI Siri Google (Amazon) (Apple) Question answering Question answering h7p://youtu.be/WFR3lOm_xhE?t=20s Connecons to Related Fields • Informaon retrieval • Natural language processing • Databases • Machine learning • Ar%ficial intelligence Queson Answering Types of Ques%ons in Modern Systems • Factoid quesons – Who wrote “The Universal Declaraon of Human Rights”? – How many calories are there in two slices of apple pie? – What is the average age of the onset of au%sm? – Where is Apple Computer based? • Complex (narrave) ques%ons: – In children with an acute febrile illness, what is the efficacy of acetaminophen in reducing fever? – What do scholars think about Jefferson’s posi%on on dealing with pirates? Commercial systems: mainly factoid quesons Where is the Louvre Museum In Paris, France located? What’s the abbreviaon for L.P. limited partnership? What are the names of Odin’s Huginn and Muninn ravens? What currency is used in China? The yuan What kind of nuts are used in almonds marzipan? What instrument does Max drums Roach play? What is the telephone number 650-723-2300 Paradigms for QA • IR-based approaches – TREC; Google • Knowledge-based approaches – Apple Siri; Wolfram Alpha; Amazon Evi • Hybrid approaches – IBM Watson Many ques%ons can already be answered by web search • a IR-based Ques%on Answering • a IR-based Factoid QA Document DocumentDocumentDocument Document Document Indexing Answer Passage Question Retrieval Processing Docume Document Query Document Document
    [Show full text]
  • Knowledge Vault: a Web-Scale Approach to Probabilistic Knowledge Fusion
    Knowledge Vault: A Web-Scale Approach to Probabilistic Knowledge Fusion ∗ Xin Luna Dong , Evgeniy Gabrilovich, Geremy Heitz, Wilko Horn, Ni Lao, y Kevin Murphy , Thomas Strohmann, Shaohua Sun, Wei Zhang Google, 1600 Amphitheatre Parkway, Mountain View, CA 94043 {lunadong|gabr|geremy|wilko|nlao|kpmurphy|tstrohmann|sunsh|weizh}@google.com ABSTRACT In recent years, several large-scale knowledge bases (KBs) Recent years have witnessed a proliferation of large-scale have been constructed, including academic projects such as knowledge bases, including Wikipedia, Freebase, YAGO, Mi- YAGO [39], NELL [8], DBpedia [3], and Elementary/ Deep- Dive [32], as well as commercial projects, such as those by crosoft's Satori, and Google's Knowledge Graph. To in- 1 2 3 crease the scale even further, we need to explore automatic Microsoft , Google , Facebook , Walmart [9], and others. methods for constructing knowledge bases. Previous ap- (See Section 7 for a detailed discussion of related work.) proaches have primarily focused on text-based extraction, These knowledge repositories store millions of facts about which can be very noisy. Here we introduce Knowledge the world, such as information about people, places and Vault, a Web-scale probabilistic knowledge base that com- things (generically referred to as entities). bines extractions from Web content (obtained via analysis of Despite their seemingly large size, these repositories are text, tabular data, page structure, and human annotations) still far from complete. For example, consider Freebase, the with prior knowledge derived from existing knowledge repos- largest open-source knowledge base [4]. 71% of people in Freebase have no known place of birth, and 75% have no itories.
    [Show full text]