Patent application EP19163499A (EP), filed 2019-03-18
Publication number: EP3543876A1
Title: MODEL-AGNOSTIC VISUALIZATIONS USING LINEAR PROGRAMMING APPROXIMATION
Abstract: A method of determining influence of language elements in script to an overall classification of the script includes performing a sentiment analysis of the language elements. In some instances, for example, in a conversation, the language elements and turns within the conversation (e.g., in a chat bot) are analyzed for their influence in escalation or non-escalation of the conversation to a higher level of resolution, e.g., to a human representative or manager.
IPC codes: G06F  17/    27            A I
G06N  20/    00            A I
Claims: number: 1
text: A method of determining influence of language elements in script to an overall classification of the script, the language elements including a plurality of turns, the method including includes:
number: 2
text: The method of claim 1, wherein the script is a conversation
number: 3
text: The method of claim 1, further comprising defining a set of distinct perturbations
number: 4
text: The method of claim 1, wherein, given the conversation C = T 1 ... T N ,
number: 5
text: The method of claim 4, further comprises representing importance of each turn by finding turn weights w = {w1, ..., wN} such that for each perturbation
number: 6
text: The method of claim 5, further comprising minimizing ∑<P∈P C>|w·PT-CLASS(P)|, where ∑ ranges over all distinct perturbations of C, subject to the condition that wi > 0 for all turns Ti.
number: 7
text: The method of claim 5, further comprising minimizing ∑ P ∈ P C w ⋅ P T − CLASS P 2
number: 8
text: The method of claim 5, wherein finding the weights w = {w1, ..., wN} for given a conversation C = T 1 ... T N ,
number: 10
text: The method of claim 9, further comprising finding a weight vector according to min w ∈ 0 1 N ∑ p ∈ P C w . P T − CLASS P 2 s . t . w i ∈ ( 0 , 1 ] for all i ∈ 1 ... N
number: 11
text: 10. The method of claim 1, wherein analyzing comprises: solving at least one linear programming approximation.
number: 12
text: 11. The method of claim 10, further comprising solving two linear programming approximations.
number: 13
text: 12. A non-transitory computer readable storage medium having stored therein software executable to perform steps comprising:
number: 14
text: 13. A graphical user interface comprising a visual representation of a classifier resulting from performing a perturbation of the language elements by removing a subset of the language elements; and analyzing the resulting classification to determine if the removed subset of the language elements causes a change in classifier outcome; and further comprising a visual scale indicative of the importance of the language elements to the result of the classifier.
Office action: search_report, dated 2019-09-25
Rejection reasons: novelty_epc_54
Prior art cited: ref_id: - MARTENS D ET AL: "Explaining Data-Driven Document Classifications", MIS QUARTERLY, 2014, XP055609297, ISSN: 0276-7783, DOI: 10.25300/MISQ/2014/38.1.04
ref_type: npl
severity: background
ref_id: - RIBEIRO M T ET AL: ""Why Should I Trust You?"", PROCEEDINGS OF THE 22ND ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD '16, ACM PRESS, NEW YORK, NEW YORK, USA, 13 August 2016 (2016-08-13), pages 1135 - 1144, XP058276906, ISBN: 978-1-4503-4232-2, DOI: 10.1145/2939672.2939778
ref_type: npl
severity: background
ref_id: - ZICHAO YANG ET AL: "Hierarchical Attention Networks for Document Classification", PROCEEDINGS OF THE 2016 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES, 2016, Stroudsburg, PA, USA, pages 1480 - 1489, XP055539296, DOI: 10.18653/v1/N16-1174
ref_type: npl
severity: background
ref_id: [XPA]     - FREEMAN C ET AL: "Paying Attention to Attention: Highlighting Influential Samples in Sequential Analysis", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 6 August 2018 (2018-08-06), XP081412765
ref_type: npl
severity: background
ref_id: - MARTENS D ET AL, "Explaining Data-Driven Document Classifications", MIS QUARTERLY, (2014), doi:10.25300/MISQ/2014/38.1.04, ISSN 0276-7783, XP055609297 [X] 1,12,13 * section "Introduction" * * section "Explaining the classification of documents" * * section "Finding document classification explanations" * [A] 2-11
ref_type: npl
severity: novelty_destroying
ref_id: - RIBEIRO M T ET AL, ""Why Should I Trust You?"", PROCEEDINGS OF THE 22ND ACM SIGKDD INTERNATIONAL CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, KDD '16, ACM PRESS, NEW YORK, NEW YORK, USA, (20160813), doi:10.1145/2939672.2939778, ISBN 978-1-4503-4232-2, pages 1135 - 1144, XP058276906 [X] 1,12,13 * abstract * * sections 1, 2 * * sections 3.1 to 3.5, 5.1 * * figures 1, 2 * [A] 2-11
ref_type: npl
severity: novelty_destroying
ref_id: - ZICHAO YANG ET AL, "Hierarchical Attention Networks for Document Classification", PROCEEDINGS OF THE 2016 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES, Stroudsburg, PA, USA, (2016), doi:10.18653/v1/N16-1174, pages 1480 - 1489, XP055539296 [A] 1-13 * sections 1, 2.2, 3.6; figure 6 *
ref_type: npl
severity: background
ref_id: - FREEMAN C ET AL, "Paying Attention to Attention: Highlighting Influential Samples in Sequential Analysis", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, (20180806), XP081412765 [XP] 1,2,12,13 * sections 1-3; table 1 * [A] 3-11
ref_type: npl
severity: novelty_destroying
Final disposition: pending (2019-09-25)