5 Lessons I’ve Learned Tackling Product Matching for E-commerce

Jul 2017

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MLR Convention Centre, Whitefield, Bengaluru,

##Theme and format
The Fifth Elephant 2017 is a four-track conference on:

Data engineering – building pipelines and platforms; exposure to latest open source tools for data mining and real-time analytics.
Application of Machine Learning (ML) in diverse domains such as IOT, payments, e-commerce, education, ecology, government, agriculture, computational biology, social network analysis and emerging markets.
Hands-on tutorials on data mining tools, and ML platforms and techniques.
Off-the-record (OTR) sessions on privacy issues concerning data; building data pipelines; failure stories in ML; interesting problems to solve with data science; and other relevant topics.

The Fifth Elephant is a conference for practitioners, by practitioners.

Talk submissions are now closed.

You must submit the following details along with your proposal, or within 10 days of submission:

Draft slides, mind map or a textual description detailing the structure and content of your talk.
Link to a self-record, two-minute preview video, where you explain what your talk is about, and the key takeaways for participants. This preview video helps conference editors understand the lucidity of your thoughts and how invested you are in presenting insights beyond your use case. Please note that the preview video should be submitted irrespective of whether you have spoken at past editions of The Fifth Elephant.
If you submit a workshop proposal, you must specify the target audience for your workshop; duration; number of participants you can accommodate; pre-requisites for the workshop; link to GitHub repositories and documents showing the full workshop plan.

##About the conference
This year is the sixth edition of The Fifth Elephant. The conference is a renowned gathering of data scientists, programmers, analysts, researchers, and technologists working in the areas of data mining, analytics, machine learning and deep learning from different domains.

We invite proposals for the following sessions, with a clear focus on the big picture and insights that participants can apply in their work:

Full-length, 40-minute talks.
Crisp, 15-minute talks.
Sponsored sessions, of 15 minutes and 40 minutes duration (limited slots available; subject to editorial scrutiny and approval).
Hands-on tutorials and workshop sessions of 3-hour and 6-hour duration where participants follow instructors on their laptops.
Off-the-record (OTR) sessions of 60-90 minutes duration.

##Selection Process

Proposals will be filtered and shortlisted by an Editorial Panel.
Proposers, editors and community members must respond to comments as openly as possible so that the selection processs is transparent.
Proposers are also encouraged to vote and comment on other proposals submitted here.

Selection Process Flowchart

We will notify you if we move your proposal to the next round or reject it. A speaker is NOT confirmed for a slot unless we explicitly mention so in an email or over any other medium of communication.

Selected speakers must participate in one or two rounds of rehearsals before the conference. This is mandatory and helps you to prepare well for the conference.

There is only one speaker per session. Entry is free for selected speakers.

##Travel grants
Partial or full grants, covering travel and accomodation are made available to speakers delivering full sessions (40 minutes) and workshops. Grants are limited, and are given in the order of preference to students, women, persons of non-binary genders, and speakers from Asia and Africa.

##Commitment to Open Source
We believe in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like for it to be available under a permissive open source licence. If your software is commercially licensed or available under a combination of commercial and restrictive open source licences (such as the various forms of the GPL), you should consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support the conference in return for giving you an audience. Your session will be marked on the schedule as a “sponsored session”.

##Important Dates:

Deadline for submitting proposals: June 10
First draft of the coference schedule: June 20
Tutorial and workshop announcements: June 20
Final conference schedule: July 5
Conference dates: 27-28 July

##Contact
For more information about speaking proposals, tickets and sponsorships, contact info@hasgeek.com or call +91-7676332020.

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The Fifth Elephant

The Fifth Elephant - known as one of the best data science and Machine Learning conference in Asia - has transitioned into a year-round forum for conversations about data and ML engineering; data science in production; data security and privacy practices. more

All submissions

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This submission has been added to the schedule

5 Lessons I’ve Learned Tackling Product Matching for E-commerce

Submitted Apr 29, 2017

Section: Full talk for data engineering track Technical level: Intermediate

Product matching is the challenge of examining two different representations of retail products (think items that you see on e-commerce websites) and determining whether they both refer to the same product. Tackling this problem requires a mix of NLP (to deal with text data), computer vision (to deal with product images), ontology management and more (to ingest a host of other signals on offer).

I’ve been working on this problem in various capacities for a few years now at Semantics3. During this period, I’ve made a fair number of mistakes which in turn have taught me useful lessons about applying deep/machine learning in an industry setting.

During this talk, I’d like to walk you through 5 specific scenarios in which I attempted to achieve a specific goal in the context of product matching, but ran into an unexpected problem that threw a spanner in the works. I’ll then talk about the root cause that sprouted the problem in the first place and the lesson I learned having made this discovery. Where relevant, I’ll bring in examples from outside the retail domain to broaden the perspective offered.

The goal of the talk isn’t to provide a guidebook for solving the product matching problem - the goal is to give you insight into the ups and downs of working through a specific data-science problem, and in the process, delivering packaged lessons that you could potentially draw on in your own field of work.

Outline

Slides: https://docs.google.com/presentation/d/e/2PACX-1vQXiUXFJlyY15Q9y4dzgQZRrN808r2x6jm-5oahtczE_Mb4MpzErXychm2JXccGSS-3563Dk5QgPT-H/pub

Requirements

Basic understanding of deep learning and experience working on real-world problems is ideal. Beginners should be able to follow.

Speaker bio

Govind is a co-founder of Semantics3. Semantics3 provides Data APIs and AI APIs for e-commerce focused companies to make better decisions and grow their businesses. We’re a 5+ year old Y Combinator backed startup based in Bengaluru, San Francisco and Singapore.

Our data-science team works on e-commerce data problems like product categorization, product matching, named entity recognition and unsupervised content extraction.