Call for Participation: CIKM 2023 Industry Day

You can still register in-person for the industry day at the ACM Conference on Information and Knowledge Management (CIKM) in Birmingham, UK. The industry day takes place October 22 at the University of Birmingham campus. It offers a range of industry-related and high-profile talks by experts in the field.

Additionally, you can register online for the main CIKM event on October 23-25, 2023.

Industry Day In-Person and CIKM Online Registration: https://cikm2023.org/registration-rates

The following talks are scheduled for the industry day (please also see https://cikm2023.org/industry-day-programme):

Application and Evaluation of Large Language Models for the Generation of Survey Questions Antonio Maiorino, Zoe Padgett, Chun Wang, Misha Yakubovskiy and Peng Jiang

Unleashing the Power of Large Language Models for Legal Applications Dell Zhang, Alina Petrova, Dietrich Trautmann and Frank Schilder

Harnessing GPT for Topic-Based Call Segmentation in Microsoft Dynamics 365 Sales Itzik Malkiel, Uri Alon, Yakir Yehdua, Shahar Keren, Oren Barkan, Royi Ronen and Noam Koenigstein Astrolabe: Visual Graph Database Queries with Tabular Output Michael Miller

Type theory as a unifiying paradigm for data models Christoph Dorn and Haikal Pribadi

Proactive and Automatic Detection of Product Misclassifications at Massive Scale Ling Jiang, Xiaoyu Chu, Saaransh Gulati, Pulkit Garg, Andrew Borthwick and Gang Luo

Vigil: Effective end-to-end monitoring for large-scale recommender systems at Glance Priyansh Saxena and Manisha R Comparative Analysis of Open Source and Commercial Embedding Models for Question Answering Georgios Balikas

Comparing Fine-Tuned Transformers and Large Language Models for Sales Call Classification: A Case Study Roy Eisenstadt, Abedelkader Asi and Royi Ronen

From User Activity Traces To Navigation Graph for software enhancement: An Application Of Graph Neural Network (GNN) On a Real-world Non-attributed Graph Boukhraouba Ikram

Practical Lessons Learned From Detecting, Preventing and Mitigating Negative Experiences in Facebook Prathyusha Senthil Kumar LAMM: Language Aware Active Learning for Multilingual Models Ze Ye, Dantong Liu, Kaushik Pavani and Sunny Dasgupta

Prod2Vec-Var: A Session Based Recommendation System with Enhanced Diversity Hacer Turgut, Tan Doruk Yetki, Tayfun Arda Yücel and Ömür Bali

RT2S: A Framework for Learning with Noisy Labels Indranil Bhattacharya, Ze Ye, Kaushik Pavani and Sunny Dasgupta

Looking forward to seeing you in Birmingham!