Yang's research group wiki

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======Volunteer Matching for Social Work======

[[volunteer_data:top| Volunteer Data Analysis Home]]

====Project Goals====
  - **volunteer to social work case matching**: assign volunteers to social work case to maximize user satisfaction and global utility. (G1)
  - **volunteer user categorization (profiling)**: identify user groups to apply precise content targeting and mobilization/management strategy (G2)


Solving G2 will help G1 by improving matching result given sparse and incomplete data. Ideally both tasks can be accomplished in a joint model to ensure optimality.

====Related topics====
  * personnel assignment problem
  * bilateral/two-way recommendation problem
  * user categorization/profiling for recommendation


====Weekly Progress====

=== Meeting: March 16, 2024 ===
  * === **Attendees:** ===
  * professor Yang Li, Yuanbo Tang, Dongdong Zhang, Yang Chen, Kaixuan Gan (16:00-17:00)
  * === **Discussion** ===
  * Kaixuan presented a report of his work in the last week.H1: Data processing and analysis, H2: Dimensionality reduction and clustering of volunteers'data
  * Dongdong shared new data and discuss aim of volunteer_matching program and the plan of future work

  * === **Future plan** ===
  * Improvement of dimensionality reduction methods (LDA dimensionality reduction) and clustering methods.
  * Further acquisition of behavioral data.
  * Hoping to better analyze, predict, and match volunteers with corresponding tasks through data integration.
  * Recommendation System Related Literature Review.

=== Meeting: March 23, 2024 ===
  * === **Attendees:** ===
  * professor Yang Li, Yuanbo Tang, Dongdong Zhang, Yang Chen, Kaixuan Gan (16:00-17:00)
  * === **Discussion** ===
  * Kaixuan presented a report of his work in the last week.H1: Introduction to recommendation system related technologies
  * Yang Chen shared new data's organization and analysis
  * professor Yang Li introduced some related topics helpful to Volunteer Matching work 
  * Discuss the plan of future literature review and data processing

  * === **Future plan** ===
  * Literature Review on personnel assignment problem and user categorization/profiling for recommendation
  * Further acquisition of Negative feedback behavior data.
  * Topic analysis of different data.
  * Mind map of existing data.

=== Meeting: March 30, 2024 ===

  * {{:volunteer_data:3.30report.pptx}}
  *   * === **Attendees:** ===
  * professor Yang Li, Yuanbo Tang, Yang Chen, Kaixuan Gan (16:00-17:00)
  * === **Discussion** ===
  * Yuanbo presented a report of his work in the last week.H1: The topic analysis of existing textual data.
  * Yang Chen shared the potential acquisition of more valuable data in the future.
  * Discuss the plan of future data processing and topic analysis

  * === **Future plan** ===
  * Literature Review on personnel assignment problem and user categorization/profiling for recommendation
  * Further acquisition of data.
  * Topic analysis of further data.

=== Meeting: April 6, 2024 ===
  *   * === **Attendees:** ===
  * professor Yang Li, Yuanbo Tang, Kaixuan Gan (16:30-17:30)
  * === **Discussion** ===
  * Kaixuan presented a report of his work in the last week.H1: Using autoencoder for dimensionality reduction and clustering.
  * professor Yang Li gave some advice on analysis of clustering results.
  * Discuss the plan of future data processing.

  * === **Future plan** ===
  * Literature Review on personnel assignment problem and user categorization/profiling for recommendation
  * Quantitative analysis of clustering results.
  * Performing one-hot encoding on categorical data.

=== Meeting: April 13, 2024 ===
  * {{ :volunteer_data:4.13report.pptx |}}
  *   * === **Attendees:** ===
  * professor Yang Li, Yuanbo Tang, Dongdong Zhang, Yang Chen，Qitai Tan， Kaixuan Gan (16:00-17:00)
  * === **Discussion** ===
  * Kaixuan presented a report of his work in the last week.H1: Using autoencoder for dimensionality reduction and clustering.
  * professor Yang Li gave some advice on data processing.
  * Discuss the plan of future acquisition of data.

  * === **Future plan** ===
  * Literature Review on recommendation system.
  * Perform clustering analysis again after adding more data.
  * Further acquisition of data.