A Graph Database Model for Knowledge Extracted from Place Descriptions

Hao Chen, Maria Vasardani, Stephan Winter, Martin Tomko
2018 ISPRS International Journal of Geo-Information  
Everyday place descriptions provide a rich source of knowledge about places and their relative locations. This research proposes a place graph model for modeling this spatial, non-spatial, and contextual knowledge from place descriptions. The model extends a prior place graph, and overcomes a number of limitations. The model is implemented using the Neo4j graph database, and a management system has also been developed that allows operations including querying, mapping, and visualizing the
more » ... knowledge in an extended place graph. Then three experimental tasks, namely georeferencing, reasoning, and querying, are selected to demonstrate the superiority of the extended model. Though these place graphs are place knowledge bases [9, 10] , the triplets that build them are stripped off of much of their conversational contexts. It is, therefore, possible to find incompatible information in a place graph, especially if the graph is constructed from combining place descriptions with different contexts. For example, it is perfectly possible to collect seemingly contradicting triplets such as and from two place descriptions, since the use of the different distance prepositions is context-dependent. Storing such triplets in a place graph without further capturing their original contexts could result in loss of information and misinterpretation. Moreover, the interpretation of spatial relations found in NL place descriptions often relies on information that is not explicit and has to be inferred. For example, people infer whether the reference frame of relative direction relations, as in is intrinsic or relative. While people are often capable of such inferences, the basic place graph only stores explicit information. The above place graph also do not consider place semantics or place-related human activities, which are valuable for further spatial reasoning and query answering. Consequently, the usefulness of the original place graph model from a knowledge base perspective is restricted. Currently, query answers are provided by matching the values of certain property keys and by graph traversing, without filtering for context, inferences, or semantics, while the interpretation of spatial relationships such as relative directions or qualitative distances is limited. This work reorganizes, revises and extends the original place graph model. The goal is to capture information from place descriptions that is useful, but lost during the triplet extraction. The hypothesis of this research is that, the extended place graph overcomes significant limitations of the original model in georeferencing, reasoning, and querying tasks. Specifically, the extended model can be used to derive more constrained locations of places for georeferencing. It captures additional information such as reference frames to be used in maintaining relational consistency, and it is capable of answering additional spatial queries. Accordingly, the contributions of this research include: 1. The identification of eight types of information that are either embedded in place descriptions or in external context and have not been captured by the original place graph model. 2. An extended place graph model that represents such information and enables future tracing as well as querying. 3. The implementation of the extended place graph into a graph database management system, which allows operations including querying, visualizing, and mapping. 4. The demonstration of how the extended model overcomes limitations of the original place graph in georeferencing, reasoning, and querying tasks based on three experiments. The remainder of this paper is structured as follows: In Section 2 related work on place, place models, place descriptions, and place graphs is provided. Section 3 identifies the information not captured in the original place graph model, and introduces the extended model. Section 4 looks at the extended model's implementation and three experiments demonstrating its superiority. In Section 5 the experimental results are discussed, and the highlights of this work are presented in the concluding Section 6. Related Work Place based research is an emerging field in GIScience with importance widely acknowledged (e.g., [11] [12] [13] ). The purpose is to smooth and simplify human-computer interaction by capturing, modelling, and utilizing place-related information. For example, Egenhofer and Mark suggested Naive Geography in order to capture and reflect the way that non-experts think and reason about space and time [14] . In this section, related work about how places are conceptualized, modelled in information systems, and communicated in descriptions is discussed. Place as a cognitive concept Space and place are two fundamental concepts in geography, and more broadly in social sciences, humanities, and information science [15] . Although the concept of place has existed for Preprints (www.preprints.org) | NOT PEER-REVIEWED | Posted: 16
doi:10.3390/ijgi7060221 fatcat:7catscbto5bchliameeej4fdnu