The Fifth Elephant 2016

India's most renowned data science conference

The Fifth Elephant is India’s most renowned data science conference. It is a space for discussing some of the most cutting edge developments in the fields of machine learning, data science and technology that powers data collection and analysis.

Machine Learning, Distributed and Parallel Computing, and High-performance Computing continue to be the themes for this year’s edition of Fifth Elephant.

We are now accepting submissions for our next edition which will take place in Bangalore 28-29 July 2016.

Tracks

We are looking for application level and tool-centric talks and tutorials on the following topics:

  1. Deep Learning
  2. Text Mining
  3. Computer Vision
  4. Social Network Analysis
  5. Large-scale Machine Learning (ML)
  6. Internet of Things (IoT)
  7. Computational Biology
  8. ML in healthcare
  9. ML in education
  10. ML in energy and ecology
  11. ML in agriculrure
  12. Analytics for emerging markets
  13. ML in e-governance
  14. ML in smart cities
  15. ML in defense

The deadline for submitting proposals is 30th April 2016

Format

This year’s edition spans two days of hands-on workshops and conference. We are inviting proposals for:

  • Full-length 40 minute talks.
  • Crisp 15-minute talks.
  • Sponsored sessions, 15 minute duration (limited slots available; subject to editorial scrutiny and approval).
  • Hands-on Workshop sessions, 3 and 6 hour duration.

Selection process

Proposals will be filtered and shortlisted by an Editorial Panel. We urge you to add links to videos / slide decks when submitting proposals. This will help us understand your past speaking experience. Blurbs or blog posts covering the relevance of a particular problem statement and how it is tackled will help the Editorial Panel better judge your proposals.

We expect you to submit an outline of your proposed talk – either in the form of a mind map or a text document or draft slides within two weeks of submitting your proposal.

We will notify you about the status of your proposal within three weeks of submission.

Selected speakers must participate in one-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. As our budget is limited, we will prefer speakers from locations closer home, but will do our best to cover for anyone exceptional. HasGeek will provide a grant to cover part of your travel and accommodation in Bangalore. Grants are limited and made available to speakers delivering full sessions (40 minutes or longer).

Commitment to open source

HasGeek believes in open source as the binding force of our community. If you are describing a codebase for developers to work with, we’d like 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), please consider picking up a sponsorship. We recognise that there are valid reasons for commercial licensing, but ask that you support us in return for giving you an audience. Your session will be marked on the schedule as a sponsored session.

Key dates and deadlines

  • Revised paper submission deadline: 17 June 2016
  • Confirmed talks announcement (in batches): 13 June 2016
  • Schedule announcement: 30 June 2016
  • Conference dates: 28-29 July 2016

Venue

The Fifth Elephant will be held at the NIMHANS Convention Centre, Dairy Circle, Bangalore.

Contact

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

Hosted by

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

Ekta Grover

@ekta1007

Purpose, Speed & Visibility : Facilitating product discovery & engagement on a e-commerce website

Submitted Apr 29, 2016

Each product on an ecommerce website has an opportunity to sell and market dynamics determines what’s selling and at what speed . This has Merchandising implications for stock re-fill, flash sales, promotions & special events - along with the actions a merchant’s platform team takes in anticipation for such events. By reverse engineering this quantitatively, and tuning the proprietary Search ranking signals, we can meet a Merchant’s business goal both from a discoverability and bottom-line incremental revenue perspective.

This session is about 2 main things –
1. Search & Personalization : Understanding a user’s footprint & quantifying the weblogs to meet two broad goals - facilitating discoverability and driving user engagement .
2. Hypothesis driven engineering - 3 specific problems we solved at Bloomreach - while pushing them upward as proprietary signals in Product design

Outline

I will start with defining a user’s intent, web journey and how products sell on an ecommerce website - defining the “discoverability” and “engagement” goals. I will then introduce relevance, recall & performance/engagement based discoverability from a search ranking perspective.
Though the two goals above(discoverability & engagement) look inclusive, I will showcase using the 3 problems, how conventional metrics such as Bounce rate, product view rate, ATC rate, Conversion rate etc. can mask serious challenges that end-users face - thus opening up opportunities about a Merchant can actually address for its users.

Problem # 1 : Understanding lost carts
Data from a merchant with abandoned carts - where we figured out it was a problem with stock-replenishment of popular sizes and people were using carts to “bookmark”. While we do not control/influence a merchandiser‘s inventory - how could we change “the search storefront” (aka the search results page) - to reflect the availability factor that blended the popularity factor - also introducing the supply & demand dynamics at this point.
In the process, we ended up building a clustering solution for mapping sizes across different categories, which then fed into the availability factor.

Problem # 2 : Handling Special events - Mother’s day, Back to school, Halloween & holiday sales , special sports events etc. , Marketplace products & New launches

Using data from the sudden redirect pages that a Merchant’s platform team sets up - to understand a Merchant’s Business goals, quantitatively and then reflecting this in “discoverability” score I introduced before. This means that the evolving intent for these special events now ties to the hot products that merchandizer knows best will sell.
Also, all products are created unequal & by revisiting to a product’s purpose - we can proxy a user’s intent. Since a product only exists in the realm of a “user intent” - bootstrapping some fair impressions is more challenging than it looks.

One goal could be ensuring the new products have some impressions before they starve & set a downward spiral in the ecosystem, but this when also coupled with non-sellable/zombie products that a merchant introduces ahead of launches (eg iphone 6s, Motorola next gen etc.) skews the performance data. eg, some products get a lot of impressions, but do not sell since they are not sellable -this problem will showcase how do we flex the two uber goals of discoverability & engagement for products.

Problem # 3 : Understanding users segments on a website
We can’t fix what we don’t understand is broken. Aside of search, users use very suggestive sort parameters, dynamic filters, paginatation - this problem will showcase data about “intent classification” that helped our search tuning efforts. Brand sensitive vs. price sensitive users are a different breed - and this has search storefront implications, not just for what to show (close substitutes,complementary goods, related but neither substitutes, not complementary goods)- but also on how we measure the intent’s differently. There is no such thing as an average user, afterall.

Speaker bio

Ekta Grover is a Member Technical Staff & Data Scientist at Bloomreach Inc, a firm that helps B2B and B2C companies make their content more discoverable, relevant & personalized, while growing the bottom line for the Businesses. At Bloomreach she focuses on influencing proprietary Search ranking signals in core search, commoditizing analysis and shaping decisions that impact bottom line Business metrics for some of the largest retail merchants.

She has experience leading & building data tools in location based Mobile advertising, e-commerce, Search & Personalization. Across her professional footprint, she has worked with both Enterprise product companies (SAP, VMware) and midsize/small startups in consumer web - and has helped shape products that affects million of users and billions of dollars in incremental revenue for some of the largest e-commerce firms. She has a background in Quantitative Economics & Computer Science.

Her previous talks with HasGeek
Fifth Elephant Conference, 2014 : Experimentation to Productization : developing a Dynamic Bidding system for a location aware Mobile landscape
Pycon 2013 : Experiments in data mining, entity disambiguation and how to think data-structures for designing beautiful algorithms

Links

Slides

http://www.slideshare.net/ekta1007/facilitating-product-discovery-in-ecommerce-inventory-the-fifth-elephant-2016

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Hosted by

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