SEEN: Structured Event Enhancement Network for Explainable Need Detection of Information Recall Assistance

When recalling life experiences, people often forget or confuse life events, which necessitates information recall services. Previous work on information recall focuses on providing such assistance reactively, i.e., by retrieving the life event of a given query. Proactively detecting the need for information recall services is rarely discussed. In this paper, we use a humanannotated life experience retelling dataset to detect the right time to trigger the information recall service. We propose a pilot modelstructured event enhancement network (SEEN) that detects life event inconsistency, additional information in life events, and forgotten events. A fusing mechanism is also proposed to incorporate event graphs of stories and enhance the textual representations. To explain the need detection results, SEEN simultaneously provides support evidence by selecting the related nodes from the event graph. Experimental results show that SEEN achieves promising performance in detecting information needs. In addition, the extracted evidence can be served as complementary information to remind users what events they may want to recall. ➊ My brother decided to propose to his fiancée, Ellie. Afterward, ➋ She hosted the party in their backyard. It was so fun! They had a beautifully stocked bar with lots of alcohol. ➌ The shots and cocktails were fantastic! PRE-RETOLD STORY POST-RETOLD STORY Match Match Conflict Forgotten My brother's engagement party was hosted in my hometown. ➍ It was hosted by his fiancée, Ellen. ➎ She had it outside in her backyard. Even though it was 90 degrees, we all had so much fun ! ➏ In addition, it was also the first time that my boyfriend met my family.