A Spatial Indexing Approach for High Performance Location Based Services
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The rapid development of positioning technology, wireless communication and mobile devices has given rise to the exciting Location Based Services (LBS) thus significantly influencing existing navigational procedures. Motivated by the increasing need to search efficiently through a huge number of service locations (e.g. restaurants, hotels, shops, and more), this paper presents an efficient spatial index QR-tree, a hybrid index structure of Quadtree and R-tree, instead of the exhaustive search to improve the performance in response to user queries. QR-tree consists of two levels: the upper level is a Quadtree residing in the main memory which partitions the data space and the lower level is disk-resident R-trees assigned to the subspaces resulting from the partitioning process. Computational experiments show that the hybrid index structure is able to reduce query response time by up to 30% and achieve significant improvement on data update over the conventional indexing methods, thereby providing an effective option for efficient navigation services.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it