Book section Open Access
Query reformulation based on word embeddings: A comparative study
Panos Panagiotou; George Kalpakis; Theodora Tsikrika; Stefanos Vrochidis; Ioannis Kompatsiaris
Formulating effective queries for retrieving domain-specific content from the Web and social media is very important for practitioners in several fields, including law enforcement analysts involved in terrorism-related investigations. Query reformulation aims at transforming the original query in such a way, so as to increase the search effectiveness by addressing the vocabulary mismatch problem. This work presents a study comparing the performance of global versus local word embeddings models when applied for query expansion. Two query expansions methods are employed (i.e., CombSum and Centroid) for defining the most similar terms to each query term, based on Glove pre-trained global embeddings and local models trained on four large-scale benchmark and one terrorism-related datasets. We assessed the performance of the global and local models on the benchmark datasets based on commonly used evaluation metrics, and performed a qualitative evaluation of the respective models on the terrorism-related dataset. Our findings indicate that the local models yield promising results on all datasets.
| Name | Size | |
|---|---|---|
|
Query reformulation based on word embeddings.pdf
md5:d1a1b274a55c547cc112a79775f08162 |
563.0 kB | Download |
| All versions | This version | |
|---|---|---|
| Views | 282 | 282 |
| Downloads | 282 | 282 |
| Data volume | 158.8 MB | 158.8 MB |
| Unique views | 241 | 241 |
| Unique downloads | 277 | 277 |
- Publication date:
- April 30, 2020
- DOI:
-
- Keyword(s):
- query expansion word embeddings terrorism
- Published in:
- Technology Advances and Support for Security Practitioners, Springer.
- Grants:
-
European Commission:
-
TENSOR - Retrieval and Analysis of Heterogeneous Online Content for Terrorist Activity Recognition (700024)
- CONNEXIONs - InterCONnected NEXt-Generation Immersive IoT Platform of Crime and Terrorism DetectiON, PredictiON, InvestigatiON, and PreventiON Services (786731)
-
TENSOR - Retrieval and Analysis of Heterogeneous Online Content for Terrorist Activity Recognition (700024)
- Communities:
- License (for files):
- Creative Commons Attribution 4.0 International