Semantic MediaWiki (SMW) for Scientific Literature Management · 2021. 2. 23. · NLP Service 1 NLP Service 2 NLP Service n NLP Service Result Focused Summarization... Client - Parameter

Semantic MediaWiki (SMW) for Scientific Literature Management

Bahar Sateli, Rene Witte

Semantic Software LabDepartment of Computer Science and Software Engineering

Concordia University, Montreal

SMWCon Spring 2014

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Introduction Background System Design Application Conclusion

Outline

1 Introduction

2 Background

3 System Design

4 Application

5 Conclusion

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Introduction Background System Design Application Conclusion

Motivation

I Abundance of publications leads to bottlenecks in curating literature

I Existing bibliography management systems have limited content analysis support

I We need an environment that can encompass various activities of a researcher

I We hypothesize that our tool can improve knowledge-intensive literature analysistasks through a novel collaboration pattern between humans and AI assistants.

We envision a collaborative, wiki-based solution for the semantic management of researchliterature that integrates:

I a web-based interface

I semantic knowledge representation

I text mining for automatic content analysis

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Related Work

I Post-publication semantic analysisI WikiPapers1 uses Semantic Forms to collect literature focused on wiki research

I AcaWiki2, designed to collect summaries and literature reviews of peer-reviewedacademic research

I Pre-publication semantic enrichmentI The SALT (Groza et al., 2007) framework uses custom LATEX commands with explicit

semantics

I Our work is complementary to these efforts: we generate bibliographical andsemantic entities using human-AI collaboration

I We transform papers into queryable artifacts, while remaining amenable tohuman-created semantic annotation

1WikiPapers, http://wikipapers.referata.com2AcaWiki, http://www.acawiki.org

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Natural Language Processing (NLP)

I A branch of AI that uses various techniques to process content written in naturallanguage

I Multitude of NLP techniques exist, e.g.,

I Named Entity Recognition (e.g., finding Persons, Organizations, etc.)

I Quality Assessment

I Summarization

I Various NLP APIs (e.g., OpenCalais, GATE, . . . )

I Semantic Assistants framework

NLP Service 1

NLP Service 2

NLP Service n

NLP ServiceResult

FocusedSummarization

...Client

− Parameter− Calling an NLP Service

Word Processor

Server

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Requirements

I Centralized Repository of Knowledge (R1)The system must provide users with the ability to store raw data as well as anyinformation generated by users and analysis tools

I Automatic Text Analysis Support (R2)The proposed system must provide access to various NLP pipelines in a unifiedmanner.

I Collaborative Analysis Environment (R3)The proposed system shall provide an environment where all researchers have accessto the most up-to-date information and can keep track of content modifications.

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System Architecture

Design Decisions:

I Wiki-based Collaborative Web Interface (R3)

I Semantic MediaWiki as a Knowledge Base (R1)

I Text Mining Pipelines for Literature Analysis (R2)

Language

Descriptions

Service

Database

We

b S

erv

er

Web Server

MediaWiki Engine

Wik

i−N

LP

Co

mp

on

en

t

Ze

eva

Fa

cts

NLP Service Connector

NLP Subsystem

OntologiesWiki−NLPWiki Extensions

...

Semantic AssistantsZeeva WikiUser

Se

ma

ntic

Me

dia

Wik

i

Service Information

Service Invocation

Readability Analysis

Automatic Indexer

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Semantic Metadata Extraction

Given a paper, we are interested in extracting:

I Structural Entities, i.e., parts of text that uniquely identify a paper, like title orauthor

I Semantic (Rhetorical) Entities, i.e., parts of text that describe the contributions,claims, findings and conclusions postulated by the papers authors

:hasTitle:hasAuthor

Database

Semantic Wiki

#paper_1234

#JohnDoe "Towards a semantic ..."

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Templating Mechanism

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Automatic Processing of Publications

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Querying the Zeeva Knowledge Base

I Transform Zeeva from a collaborative analysis environment to a knowledge base

I The generated semantic metadata can be used within wiki or exported to externalapplications

I Semantic MediaWiki provides a simple inline query syntax, e.g.,

NL Question: “Give me all the contributions of Bahar Sateli.”

Corresponding SMW query:

Advantages:

1 The results queried by the system are always up-to-date

2 Lets users discover knowledge created by other users of the wiki

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Querying the Zeeva Knowledge Base

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Summary and Future Works

I The main question in this research is to evaluate whether concrete literature analysistasks can be improved using state-of-the-art semantic technologies.

I We introduced Zeeva, an empirical wiki-based evaluation platform with an extensiblearchitecture

I Identify literature analysis tasks that can improved with semantic technologies

I Develop more NLP services relevant to the context of literature analysis

I Perform an extrinsic evaluation of our hypothesis to assess the usability andefficiency of the proposed approach

http://www.semanticsoftware.info/zeeva

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