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A natural language interface (NLI) to databases is an interface that translates a natural language question to a structured query that is executable by database management systems (DBMS). However, an NLI that is trained in the general domain is hard to apply in the spatial domain due to the idiosyncrasy and expressiveness of the spatial semantics. Moreover, there are a wide range of database servers available, and a unilingual NLI model limits its practical usage. In this article, we propose to not only address the spatial domain generalization challenge, but also support multilingual back-end, i.e., supporting different query languages, such as SQL and Prolog. For the challenge of spatial semantics, we propose a spatial comprehension model that is able to recognize the meaning of spatial entities based on the semantics of context and effectively resolve the ambiguity given the spatial semantics. The spatial semantics learned from the spatial comprehension model is then injected to the natural language question to ease the burden of capturing the spatial-specific semantics. We also propose to add a prefix symbol to support the multilingual back-end (e.g., query languages). With our spatial comprehension model and symbol injections, our NLI for the spatial domain, named SpatialNLI, is able to capture the semantic structure of the question and translate it to the corresponding syntax of an executable query accurately. We also experimentally ascertain that SpatialNLI outperforms state-of-the-art methods. [ABSTRACT FROM AUTHOR]

The symbols for the new IUPAC elements named in November 2016 can introduce subtle ambiguities within cheminformatics software. The ambiguities are described and demonstrated by highlighting inconsistencies between software when handling existing element symbols. [ABSTRACT FROM AUTHOR]

This paper describes our Japanese–Chinese information retrieval system. Our system takes the “query-translation” approach. Our system employs both a more conventional bilingual Japanese–Chinese dictionary and Wikipedia for translating query terms. We propose that Wikipedia can be used as a good NE bilingual dictionary. By exploiting the nature of Japanese writing system, we propose that query terms be processed differently based on the forms they are written in. We use an iterative method for weight-tuning and term disambiguation, which is based on the PageRank algorithm. When evaluating on the NTCIR-5 test set, our system achieves as high as 0.2217 and 0.2276 in relax MAP (mean average precision) measurement of T-runs and D-runs. [Copyright &y& Elsevier]

The main problem of visual query languages for geographical data concerns query ambiguity. A query can have different visual representations, which in turn can have different interpretations. Increasing the number of query objects increases its ambiguity. This derives from the fact that a query can lead to multiple interpretations for both the system and user. The user's actions may not represent his intentions, leading the system to an incorrect interpretation. So the user cannot express his exact query and different queries must thus be formulated to achieve his goals. This paper proposes an approach that allows the user to represent only desired constraints and avoid undesired constraints in visual query representation. [ABSTRACT FROM AUTHOR]

This paper defines and demonstrates four philosophies for processing queries on tree structures; shows that the data semantics of queries should be described by designating sets of nodes from which values for attributes may be returned to the data consumer; shows that the data semantics of database processing can be specified totally independent of any machine, file structure, or implementation; shows that set theory is a natural and effective vehicle for analyzing the semantics of queries on tree structures; and finally, shows that Bolts is an adequate formalism for conveying the semantics of tree structure processing. [ABSTRACT FROM AUTHOR]