# A Reputation Model of OSM Contributor Based on Semantic Similarity of Ontology Concepts
###### Abstract
However, the above evaluation methods of contributor's reputation have their advantages and disadvantages. [PERSON] et al. proposed a reputation model which mentioned three similarities, including geometry, topology, and semantics, but the semantics are not used in actual calculation models and experiments. In the editing process, there are frequently many modifications made by contributors only to object tags. In this case, only the semantic properties of the object are changed, while the geometric and topological properties remain unchanged. If the semantic similarity between object versions is ignored, the evaluation of the volunteer's will be inaccurate. Many scholars have shown that the contributors' reputations have an important impact on the quality of the data they produce. It can be used to evaluate the data quality. However, there is still a lack of research on the contributor's reputation considering the semantic similarity of the object's versions. Aimed at the existing problems, this paper proposes a reputation model of OSM contributor based on semantic similarity of ontology concepts. Firstly, this model analyzes the composition of the contributor's reputation, and divides the contributor's reputation into two parts: evaluation reputation and initial reputation [12]. The initial reputation is determined by the classified contributor's categories, and the evaluation reputation is based on semantic similarity of ontology concept, geometric similarity, and topological similarity. Then, the initial reputation and the evaluation reputation are combined to obtain the contributor's reputation. Finally, the reputation evaluation model proposed in this paper is verified by taking the historical data of Rutland County, England, in OSM as an example. The experimental results show that the evaluation model proposed in this paper can more truly evaluate the quality of users' contribution objects and verify the effectiveness of the model. The main contributions of this paper are as follows:  
1. Ontology-related research in the field of knowledge is used in this study, constructing the volunteered geographic information ontology and establishing a semantic similarity evaluation model for evaluating volunteer contributed objects, then combining the semantic similarity of ontology concept, geometric similarity, and topological similarity to obtain the contributor's evaluation reputation;
2. An evaluation method of the contributor's initial reputation is proposed. Firstly, contributors are classified by the improved WPCA-based feature dimension reduction and classification method. Then, an initial reputation is set for every OSM user in each class according to these categories and related research results. The effectiveness of this method is verified by experiments;
3. A comprehensive evaluation method of the contributor's reputation is proposed. This method more successfully combines initial reputation and evaluation reputation. With the increase of the contributor's reputation evaluation, the weight of the initial reputation becomes smaller;
4. The validity of the contributor's reputation model proposed in this paper is verified by experiments using the real historical data of OSM. The experiment shows that the contributor's reputation is essentially positively correlated with the contributor's initial reputation. Because the semantic similarity between object versions is considered, the quality of contributors' tagged data can be evaluated more accurately. This paper is divided into six sections. Related work is presented in Section 2. Then, in Section 3, we introduce the general idea of the model and the calculation method of contributor's reputation. The experimental procedure and analysis results are presented in Section 4. Section 5 discusses the advantages, limitations, and future research. Finally, Section 6 provides a conclusion.