Big Data 5 min read

Recap of Tongcheng Elong 5th Big Data Technology and Application Salon (2019)

The article reviews the 2019 Tongcheng Elong Big Data Technology and Application Salon, summarizing six expert talks on data middle platforms, intelligent marketing, real‑time recommendation, Apache Pulsar, Chinese entity recognition, and hotel ranking models, plus event highlights and future plans.

Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Tongcheng Travel Technology Center
Recap of Tongcheng Elong 5th Big Data Technology and Application Salon (2019)

Tongcheng Elong, with over 100 million paying users, hosted its 5th Big Data Technology and Application Salon on a rainy Saturday, gathering experts from various business systems and China Mobile Suzhou R&D Center to share practical cases on data platforms, recommendation systems, data mining, and more.

1. Data Middle Platform – From Theory to Product Practice – The speaker explained the concept of a data middle platform, why it is needed, and how Tongcheng Elong transformed theory into product practice, offering insights for building a data middle platform.

2. XianZhi – Intelligent Marketing Platform – Presented a user‑tag‑based dynamic segmentation system that enables real‑time group allocation, configuration, and deployment, improving operational efficiency in the post‑traffic‑bonus era.

3. Real‑Time Recommendation in Transportation Inter‑modal – Discussed performance challenges of large‑scale recommendation systems, optimization techniques, and lessons learned to maintain service quality, data integrity, and recommendation effectiveness.

4. Apache Pulsar – Next‑Generation Cloud‑Native Messaging System – Introduced Pulsar’s architecture, compared it with Apache Kafka, and highlighted its cloud‑native design, ecosystem, and community contributions.

5. Intelligent Chinese Entity Recognition System – Covered the importance of accurate entity extraction in natural language processing and shared best practices for building robust entity‑recognition models.

6. Evolution of Hotel Ranking Models – Described the progression of hotel ranking algorithms driven by massive data growth and the need for personalized, intelligent content presentation.

The event concluded with an award ceremony, a group photo, and participants sharing their impressions, expressing enthusiasm for the next edition of the salon. The presentation slides are available on the official GitHub repository: https://github.com/tongcheng-elong/dc-bigdata-meetup-2019/ .

Original Source

Signed-in readers can open the original source through BestHub's protected redirect.

Sign in to view source
Republication Notice

This article has been distilled and summarized from source material, then republished for learning and reference. If you believe it infringes your rights, please contactadmin@besthub.devand we will review it promptly.

Big Datamachine learningData Platformnatural language processingApache Pulsar
Tongcheng Travel Technology Center
Written by

Tongcheng Travel Technology Center

Pursue excellence, start again with Tongcheng! More technical insights to help you along your journey and make development enjoyable.

0 followers
Reader feedback

How this landed with the community

Sign in to like

Rate this article

Was this worth your time?

Sign in to rate
Discussion

0 Comments

Thoughtful readers leave field notes, pushback, and hard-won operational detail here.