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This document summarizes a paper on semi-automated argumentation analysis of online product reviews. The paper describes extracting argument fragments from reviews, evaluating them using formal tools, and providing semi-automated support to speed up analysts' work. The goal is to extract distributed arguments across corpora and instantiate argumentation schemes to identify pros, cons, and relationships between arguments.
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For many AI applications, a prediction is not enough. End-users need to understand the “why” behind a prediction to make decisions and take next steps. Explainable AI techniques today can provide some insight into what your model has learned, but recent research highlights the need for interactivity with XAI tools. End-users need to interact and test “what if” scenarios in order to understand and build trust with an AI system. In this talk, I’ll discuss what human-factors research tells us about human decision making and how users build trust (or lose trust) in systems. I’ll also present interaction design techniques that can be applied to XAI services design.
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User-Generated Content (UGC) such as online reviews are freely available in the web. This kind of data has
been used to support clients’ and managerial decision making in several industries, e.g. books, tourism or
hospitality. However, the challenge is how to represent this information in a structured way in order to
leverage on the information provided by the use of Web 2.0 applications. To deal with this challenge,
models and metamodels have been used to support a set of concrete applications in several sub-domains into
Computer Science and Information Systems body of knowledge (Karagiannis and Höfferer, 2006). This
paper focuses on the model-driven engineering and introduces a new multidomain and multilingual
conceptual data model to represent UGC. This model is based on a characterization of online reviews and
aims to capture all the facets of these reviews. The characterization of the reviews’ sentences extends
previous models (such as Martin and White, 2007; Ding et al., 2008; Liu, 2010). Applications build on the
model proposed in this paper may allow in-depth analysis of the fine-grained and disperse knowledge
existent in the UGC. Furthermore, as this model is domain-independent it can be used to represent multiple
types of reviews.
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This document presents a new approach for user profile modeling to improve contextual suggestions. The approach models user profiles based on the opinions and reasons users express in their reviews of different items, rather than just the categories or descriptions of liked/disliked items. Experimental results on two datasets show the opinion-based methods provide more effective suggestions than baseline category-based and description-based user profiling approaches. Future work is outlined to integrate contextual requirements into the ranking and apply the approach to other domains like local search.
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This document provides an introduction and background to hostelbench, a benchmarking service for hostels. It discusses the history of benchmarking, beginning with its origins in cobblers measuring feet and Xerox formally introducing the practice in the 1980s. The document then covers how benchmarking has evolved in the hotel industry through services like STR Global. It introduces hostelbench as seeking to provide a similar benchmarking service tailored to the hostel industry, allowing hostels to submit occupancy, rate and revenue data anonymously to generate performance reports. The intended benefits are to help hostels make more informed operational and pricing decisions through industry comparisons.
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The long, textual written report is dead, isn’t it? So how do you deliver your findings to your clients? Is it PowerPoint? An email? A spreadsheet? Post-it notes? And what do you include? Positive findings? Screenshots with callouts? Just issues? Or recommendations as well? Are they prioritized? If you ask our panelists, some of us have developed templates that we use and modify for each research activity, and others change the deliverable based on the activity and client.
1. Arguing from a Point of View
Adam Wyner1 and Jodi Schneider2
1 - Department of Computer Science, University of Liverpool
2 – Digital Enterprise Research Institute, National University of Ireland
First International Conference on Agreement Technologies
Centre for Advanced Academic Studies, University of Zagreb
Dubrovnik, Croatia
October 16, 2012
2. Overview
• Hotel reviews are a source of arguments.
• Point of view is needed to evaluate arguments such as
– The hotel is in an excellent location.
• Therefore we relativise evaluative statements based
on point of view.
• The key point: evaluative statements can be justified
using instantiated argumentation schemes relative to
a user and a domain model.
October 16, 2012 Wyner and Schneider, AT 2012 1
6. TMI
• How much 'bad' spoils what amount of 'good'?
• How do the scores relate to the content? How does the
content justify or argue for the score given?
• How do the comments relate to one another? Linear text &
lists of comments aren’t rich enough: Elaborate network of
point and counterpoint.
October 16, 2012 Wyner and Schneider, AT 2012 5
7. It's all about YOU!
People don't just want “information”
They want information that is
• relevant to them
• appeals to them
• sees things from their point of view.
October 16, 2012 Wyner and Schneider, AT 2012 6
8. Goal
• To support relativised argumentation derived from
distributed, inconsistent information.
October 16, 2012 Wyner and Schneider, AT 2012 7
9. Evaluative expressions use case
- client and travel agent -
I'm going to a conference in venue X in Valencia and need a hotel
room.
Bill
Hotel Valencia is in an excellent location.
Travel agent
Why do you say it is an excellent location?
The hotel is a kilometer from the venue X. And the hotel is in the
old part of the city.
OK, please book it.
October 16, 2012 Wyner and Schneider, AT 2012 8
10. Evaluative expressions use case
- client and travel agent -
I'm going to a conference in venue X in Valencia and need a hotel
room.
Jill
Hotel Valencia is in an excellent location.
Why do you say it is an excellent location?
The hotel is a kilometer from the venue X. And the hotel is in the
old part of the city.
But it is a noisy and trashy old part. And it is too far. Please find me
something else.
October 16, 2012 Wyner and Schneider, AT 2012 9
11. Argument evaluation is user-relative
• Bill & Jill receive the same argument from the travel
agent but evaluate it differently.
• Given the premises
– The hotel is a kilometer from the venue X. And the
hotel is in the old part of the city.
• Bill has accepted the claim
– Hotel Valencia is in an excellent location.
• Given the same premises, Jill has not accepted
the claim (and doesn't even agree with all the
premises).
• Different ways to argue for and against the same claim.
October 16, 2012 Wyner and Schneider, AT 2012 10
12. Approach
• Argumentation schemes are key
– Normative patterns of defeasible reasoning.
– Variables can be seen as targets for information
extraction. Could use text analysis to instantiate.
– Evaluate instantiated arguments using
argumentation frameworks.
• Relativise the instantiated arguments to a
user.
October 16, 2012 Wyner and Schneider, AT 2012 11
13. Argumentation Schemes Overview
• Example scheme from the literature “Credible
source”:
– Instantiated
– Abstract
– Questions used to critique the argument
• Two new schemes for our use case
– “Evaluation of location”
– “Evaluation of quality”
October 16, 2012 Wyner and Schneider, AT 2012 12
14. Argumentation scheme example
- instantiated -
• Normative patterns of defeasible reasoning:
– Dr. Rose is an expert about road safety;
– Dr. Rose asserts that having more speed cameras will save
more lives;
– Having more speed cameras will save lives is a statement
concerning road safety;
– Dr. Rose is credible about road safety;
– and Dr. Rose is reliable;
– Therefore, it is presumably true that having more speed
cameras will save more lives.
October 16, 2012 Wyner and Schneider, AT 2012 13
15. Argumentation scheme example
- abstracted -
• Normative patterns of defeasible reasoning:
– X is an expert about Y;
– X asserts Z;
– Z is a statement concerning Y;
– X is credible about Y;
– and X is reliable;
– therefore, it is presumably true that Z.
October 16, 2012 Wyner and Schneider, AT 2012 14
16. Argumentation scheme example
- critique -
• Questions used to critique the argument:
– How credible is X as an expert source?
– Is the claim about Z consistent with what other
experts assert?
– Is X’s assertion based on evidence?
– Others....
October 16, 2012 Wyner and Schneider, AT 2012 15
17. Use case elements
• New argumentation schemes:
– Evaluation of location.
– Evaluation of quality.
• Instantiate schemes relative to a user model.
• Domain and evaluative terminology.
• User model – selection from domain terminology plus
some terminology for parameters, context of
use, constraints....
October 16, 2012 Wyner and Schneider, AT 2012 16
18. User Information
In this paper, we represent user models by terminology and
instantiated schemes.
In other work, we add these components.
October 16, 2012 Wyner and Schneider, AT 2012 17
19. “Evaluation of location” arg. scheme
- abstract -
October 16, 2012 Wyner and Schneider, AT 2012 18
20. “Evaluation of location” arg. scheme
- Instantiating for Bill & Jill -
October 16, 2012 Wyner and Schneider, AT 2012 19
21. “Evaluation of quality” arg. scheme
-abstract-
October 16, 2012 Wyner and Schneider, AT 2012 20
22. “Evaluation of quality” arg. scheme
-Instantiating for Bill-
October 16, 2012 Wyner and Schneider, AT 2012 21
24. Use case elements
• Argumentation schemes:
– Evaluation of location.
– Evaluation of quality.
• Instantiate schemes relative to a user model.
• Domain and evaluative terminology.
• User model – selection from terminology and
instantiated schemes.
October 16, 2012 Wyner and Schneider, AT 2012 23
26. User-associated inference
• If the instantiations of both argumentation schemes
are acceptable to the user, then the user has a
justification to book the hotel.
• For us, the model of the user can be given in terms of
a logical language – the terminology and the
schemes instantiated with that terminology.
• Arguing about the instantiations, e.g. Jill's criticism of
the travel agent's proposition, is a meta-argument
about the contents of the user model.
October 16, 2012 Wyner and Schneider, AT 2012 25
27. Argumentation frameworks & text analysis
• This paper is part of a larger work on the argumentation
pipeline, from textual source to abstract argumentation.
• Introduces new schemes and instantiates them relative
to a user.
• Other parts:
– We have a text analytic tool (GATE) to support the
extraction of relevant information from the source.
– We have a proposal for integrating this with
argumentation frameworks.
October 16, 2012 Wyner and Schneider, AT 2012 26
28. Argumentation pipeline
Source Text
Instantiated Abstract Argumentation
No fresh orange juice at Argumentation Schemes Frameworks
breakfast and besides terrible
filter coffee extra payment for
cappuchino etc... No wifi in the
rooms (says so in
description, but still...). AS1: ....
Relate
Extract text
schemes to
Very impressive hotel with to schemes arguments.
stunning views. Staff were
attentive - especially the bell
boys. 5 min bus journey to the AS2: ....
old town or 15 min walk. The
room was very comfortable.
If u want to stay with comfort I
would never recommend this
hotel on arrival I was waiting AS3: ....
my room from 14.00 till
16.00, but again they gave me a
room with two separate beds
ignoring my comments in the
booking (one king bed and big
bathtube)
October 16, 2012 Wyner and Schneider, AT 2012 27
29. Consumer argumentation scheme
Variables in schemes as targets for extraction.
Premises:
• Camera X has property P.
• Property P promotes value V for agent A.
Conclusion:
• Agent A should Action Camera X.
October 16, 2012 Wyner and Schneider, AT 2012 28
30. Identifying and extracting text
• Annotate text:
– Simple or complex annotations.
– Highlight annotations with
– Search for and extract text by annotation.
• GATE “General Architecture for Text Engineering”.
– Works with large corpora of text.
– Rule-based or machine-learning approaches.
October 16, 2012 Wyner and Schneider, AT 2012 29
31. ,
,
October 16, 2012 Wyner and Schneider, AT 2012 30
33. An argument for buying the camera
Premises:
The pictures are perfectly exposed.
The pictures are well-focused.
No camera shake.
Good video quality.
Each of these properties promotes image quality.
Conclusion:
(You, the reader,) should buy the CanonSX220.
October 16, 2012 Wyner and Schneider, AT 2012 32
34. An argument for NOT buying the
camera
Premises:
The colour is poor when using the flash.
The images are not crisp when using the flash.
The flash causes a shadow.
Each of these properties demotes image quality.
Conclusion:
(You, the reader,) should not buy the CanonSX220.
October 16, 2012 Wyner and Schneider, AT 2012 33
35. Counterarguments to the premises of
“Don’t buy”
The colour is poor when using the flash.
For good colour, use the colour setting, not the flash.
The images are not crisp when using the flash.
No need to use flash even in low light.
The flash causes a shadow.
There is a corrective video about the flash shadow.
October 16, 2012 Wyner and Schneider, AT 2012 34
36. Argumentation Frameworks
• <Arguments, Relation>, where
arguments are atomic nodes
and the relation is attack.
• Calculate the sets of nodes that
are 'compatible'.
• Articulate nodes with a logical
language of literals and
rules, where attack is
contrariness between
Preferred Extension of the AF.
expressions of the language.
October 16, 2012 Wyner and Schneider, AT 2012 35
37. Future work
• User model formalisation and meta-argumentation.
• Text analysis for this set of data.
• Tool refinement.
• Add ontology modules to the tool.
• Multi-critierial argumentation – properties ascribed
to the argument vs. premises of the argument.
October 16, 2012 Wyner and Schneider, AT 2012 36
38. Related Papers
• Wyner, van Engers, and Hunter (2010). "Working on the Argument
Pipeline: Through Flow Issues between Natural Language
Argument, Instantiated Arguments, and Argumentation
Frameworks", Workshop on Computational Models of Natural
Argument (CMNA).
• Wyner, Schneider, Atkinson, and Bench-Capon (2012). ''Semi-
automated argumentation analysis of online product
reviews'', Conference on Computational Models of Argument
(COMMA).
• Schneider and Wyner (2012). ''Identifying consumers' arguments in
text'', Workshop on Semantic Web and Information Extraction
(SWAIE at EKAW).
• Schneider, Davis, and Wyner (2012). ''Dimensions of argumentation
in social media'', Conference on Knowledge Engineering and
Knowledge Management (EKAW).
October 16, 2012 Wyner and Schneider, AT 2012 37
39. Acknowledgements
• FP7-ICT-2009-4 Programme, IMPACT Project, Grant
Agreement Number 247228.
• Science Foundation Ireland Grant No. SFI/08/CE/I1380 (Líon-
2). Short-term Scientific Mission grant from COST Action
IC0801 on Agreement Technologies. SFI Short Term Travel
Fellowship.
October 16, 2012 Wyner and Schneider, AT 2012 38
40. Thanks for your attention!
• Questions?
• Contacts:
– Adam Wyner adam@wyner.info
– Jodi Schneider jschneider@pobox.com
October 16, 2012 Wyner and Schneider, AT 2012 39
Editor's Notes
Tuesday, October 16, 2012
This doesn’t mentionextracting arguments from source text
For or against the hotel? Or the hotel RATING?
Not sure if “Different ways to argue for and against the same claim.” is what we want…Isn’t it really that there are Different ways to EVALUATE ARGUMENTS for and against the same claim?
Any hotel domain example that would be easy here?Why not just spend more time on one of our examples? I think that would make sense….
Might focus just on this paper here
Not sure why you call this co-variance
Haven’t shown the pipeline up till now – is “middle” clear enough? Maybe this is what you say when you’re showing the pipeline? Not sure if this slide is essential then.
Pipeline picture – linear text, schemes, argument reconstruction, abstract evaluation.
Colors represent annotations in the text. We can then search for a large body of text
Leave camera implicit in the examples for brevity.
We have an argument for buying the camera, an argument for not buying the camera. They rebut each other.We have attacks on the premises for “don’t buy the camera”. The argument for not buying the camera is defeated; the argument for buying the camera stands. So you should buy the camera.