DeepDiveIntroduction

Dongfang XuPh .D student, School of Information, University of Arizona

Sept 10, 2015

Agenda

Brief IntroductionBrief Introduction

KBC modelKBC model

WorkflowWorkflow

ReferenceDeepDive: A Data Management System for Automatic Knowledge Base Construction. Ce Zhang.Ph.D. Dissertation, University of Wisconsin-Madison, 2015.

Brief Introduction

What is Deep Dive?

•DeepDive is a new type of data management system that enables

one to tackle extraction, integration, and prediction problems in a

single system.

•It is built by generalizing from experience in building more than ten

high-quality Knowledge Base Construction (KBC) systems. (Flexible

framework)

What is KBC?•Knowledge Base Construction (KBC) is the process of populating a

knowledge base (KB).

Brief Introduction

Why Deep Dive? Or Why KBC?•Its potential to answer key scientific questions.---Collect facts, contribute to scientific discoveries

• Typical knowledge base require a large amount of resource.•Common problems in scientific area.

Brief Introduction

Why Deep Dive? Or Why KBC?•Its potential to answer key scientific questions.•Typical knowledge base require a large amount of resource.•Its good performance. ---- Developer thinks about features (extraction rules), not algorithms. ---- Large amounts of data from a variety of sources; ----High quality in extracting complex knowledge and building entity relation;---- Calibrated probabilities for each assertion it makes;----Domain knowledge + framework Deep Dive = KBC system in specific domain

Brief Introduction

General description Deep Dive----The application of Relational database.

All data in Deep Dive is stored in a relational database.

----The main task it to figure out the relation & entity.

---- A selection of target facts typically defined for an IE task.

---- Multiple non-content cues such as layout information may be used to assist extraction, e.g. section headers or their layout in tabular data.

----Extract all kinds of information about the entity and relation, high data volume.

Agenda

Brief IntroductionBrief Introduction

KBC modelKBC model

WorkflowWorkflow

KBC model

Entity: An entity is a real-world person, place, or thing. ----For example, the entity “Michelle Obama 1” represents the actual entity for a

person whose name is “Michelle Obama”.Relation: A relation associates two (or more) entities.----For example, the entity “Barack Obama 1” and “Michelle Obama 1” participate

in the HasSpouse relation, which indicates that they are married.Mention: a mention is a span of text in an input file that refers to an entity or relationship.---- “Michelle” may be a mention of the entity “Michelle Obama 1.”Relation Mention: A relation mention is a phrase that connects two mentions that participate in a relation.---- “and his wife” =“Barack Obama” and “M. Obama”.

KBC model

Agenda

Brief IntroductionBrief Introduction

KBC modelKBC model

WorkflowWorkflow

Work Flow

Work Flow

Input file

Work Flow

Input file

User Schema

Work Flow

Candidate Generation Feature Extraction

Work Flow

Candidate Generation & Feature Extraction

Work Flow

Supervision(1) hand-labeling, and (2) distant supervision

Work Flow

Supervision(1) hand-labeling, and (2) distant supervision

Work Flow

Learning and InferenceIn the learning and inference phase, Deep Dive generates a factor graph.

Work Flow

Learning and Inference

DeepDive

Resourcehttp://deepdive.stanford.edu.

https://www.youtube.com/watch?v=SfkLvExfl-s

http://pages.cs.wisc.edu/~czhang/zhang.thesis.pdf

Thank you!

Q&A