Name
Abstract | ||
|---|---|---|
ABSTRACTThis paper presents a search engine system for sensor time series data and metadata in the context of building management. It takes natural language queries as input and retrieves sensor time series data, ranks them with respect to their relevance to a given query, and visualizes the results as graphs. In addition, the system allows users to interact with the search results: they can define events of interest in the visualized results and search across sensor data for time series with similar shape, i.e. the search by example scheme. We leverage both a feature based cosine similarity model and DTW to find similar time series and rank them by relevance. Our quantitative evaluations and user studies demonstrate the value of this system for managing building sensor data. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3486611.3486647 | Embedded Network Sensor Systems |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Andrew Villca-Rocha | 1 | 0 | 0.34 |
| Max Zheng | 2 | 0 | 0.34 |
| Chengzhu Duan | 3 | 0 | 0.34 |
| Hongning Wang | 4 | 925 | 54.89 |