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This paper aims to serves two main purposes: First, it seeks to provide an overview of the location hierarchy from the highest divisions (continents) to the lowest divisions (wards, villages) in reality and in the Wikipedia pages. Secondly, it aims to introduce an approach to building a geographical ontology from Wikipedia.

The paper first reviews existing applications which extract information from Wikipedia and use it as a data resource to develop natural language processing tools. The paper also reviews the structure of Wikipedia pages which show the location's information. Based on the analysis, the paper then proposes an approach to extract location hierarchy as well as geographical characteristics for the geo‐ontology. The approach also rebuilds the relations between locations in the ontology.

Existing location name systems are mainly based on probabilistic locations, which are mined from the data and they lack the administrative relations between locations for full levels and all countries and territories. The literature review in geographical hierarchy and using Wikipedia for natural language processing tasks offers an approach to build a geographical ontology from Wikipedia pages. The proposed approach is believed to be the first which provides a full geo‐ontology for all countries.

The paper builds a geo‐ontology with full levels for all countries and territories. The administrative relations between locations are needed for real‐world applications.

The comprehensive overview on existing work on geo‐ontology provides a valuable reference for researchers and system developers in related research communities. The proposed approach to build a geographical ontology by using the Wikipedia offers a promising alternative to build a knowledge system from free online multi‐language encyclopedia.

Geographical query formulation is one of the key difficulties for users in search engines. The purpose of this study is to improve geographical search by proposing a novel geographical query reformulation (GQR) technique using a geographical taxonomy and word senses.

This work introduces an approach for GQR, which combines a method of query components separation that uses GeoNames, a technique for reformulating these components using WordNet and a geographic taxonomy constructed using the latent semantic analysis method.

The proposed approach was compared to two methods from the literature, using the mean average precision (MAP) and the precision at 20 documents (P@20). The experimental results show that it outperforms the other techniques by 15.73% to 31.21% in terms of P@20 and by 17.81% to 35.52% in terms of MAP.

According to the experimental results, the best created taxonomy using the geographical adjacency taxonomy builder contains 7.67% of incorrect links. This paper believes that using a very big amount of data for taxonomy building can give better results. Thus, in future work, this paper intends to apply the approach in a big data context.

Despite this, the reformulation of geographical queries using the new proposed approach considerably improves the precision of queries and retrieves relevant documents that were not retrieved using the original queries. The strengths of the technique lie in the facts of reformulating both thematic and spatial entities and replacing the spatial entity of the query with terms that explain the intent of the query more precisely using a geographical taxonomy.

The purpose of this paper is to describe the development of a knowledgebase supporting a prototype Europe‐wide time‐spatial search interface for historical resources. It discusses how this structure could be used to access other types of digital heritage content.

By using a relational database with spatial capabilities, a multi‐lingual search structure has been created which supports a temporal map and a facetted browser, collaborative facilities and a heritage resource viewer, with links to online catalogues.

Combining data from three states with very different histories identified the strengths and weaknesses of the approach. The framework's flexibility means it could easily be re‐purposed to support front ends to other types of cultural content.

Due to the variability in the administrative unit source data, its initial integration required significant manipulation to achieve consistency; however, the benefits of data assimilation ensure the base framework is as efficient as possible.

Usage levels of on‐line cultural resources will be far higher if ordinary users can access them via access routes which have meaning for them, such as by locality/place. Ontology‐based geographical frameworks are much easier to search by place name than are conventional GIS systems, and vastly more accessible to search engines.

This interface demonstrates the potential for integrating data from any number of different national organisations into a single user tool. It also highlights the potential for utilising the underlying structure in multiple contexts.

Search engines and web applications have evolved to be more tailored toward individual user’s needs, including the individual’s personal preferences and geographic location. By integrating the free Google Maps Application Program Interface with locally stored metadata, the author created an interactive map search for users to locate, and navigate to, destinations on the University of New Mexico (UNM) campus. The purpose of this paper is to identify the characteristics of UNM map search queries, the options and prioritization of the metadata augmentation, and the usefulness and possible improvement of the interface.

Queries, search date/time, and the number of results found were logged and examined. Queries’ search frequency and characteristics were analyzed and categorized.

From November 1, 2012 to September 15, 2013, the author had a total 14,097 visits to the SearchUNM Maps page (http://search.unm.edu/maps/). There were total 5,868 searches (41 percent of all the page visits), and out of all the search instances, 2,297 of them (39 percent) did not retrieve any results. By analyzing the failed queries, the author was able to develop a strategy to increase successful searches.

Many academic institutions have implemented interactive map searches for users to find locations and navigate on campus. However, to date there is no related research on how users conduct their searches in such a scope. Based on the query analysis, this paper identifies user’s search behavior and discusses the strategies of improving searches results of campus interactive maps.

This study aims to explore the reusing of Dublin core metadata initiative (DCMI) metadata terms on the linked open vocabulary (LOV) platform in the linked data environment to offer a better understanding of the reusing behaviour during the process of vocabulary construction and further explain why DC has become a popular vocabulary.

The authors selected LOV, as a typical linked data platform. The SPARQL language was used to acquire and parse data to examine the reuse types of DCMI terms, the reuse distribution of classes and properties in different semantic relation types among vocabularies, the subject and size of the reused vocabularies and the correlation between vocabulary reuse and data set reuse.

Results showed that DCMI metadata terms were reused by 83.7% of LOV vocabularies and became the core nodes on the vocabulary-linked network. Among the six relationships between vocabularies and the DCMI metadata terms, the metadata relationship is the most frequently used. DCMI metadata terms are reused by small- and medium-sized vocabularies and are not limited to subject domain.

This is one of the first studies focussing on the roles of DCMI metadata terms in vocabulary reusing. Furthermore, it provides a systematic view of how these DCMI terms participate in the construction of other vocabularies and in features of reused vocabularies.

The purpose of this paper is to analyse the global scientific outputs of ontology research, an important emerging discipline that has huge potential to improve information understanding, organization, and management.

This study collected literature published during 1900-2012 from the Web of Science database. The bibliometric analysis was performed from authorial, institutional, national, spatiotemporal, and topical aspects. Basic statistical analysis, visualization of geographic distribution, co-word analysis, and a new index were applied to the selected data.

Characteristics of publication outputs suggested that ontology research has entered into the soaring stage, along with increased participation and collaboration. The authors identified the leading authors, institutions, nations, and articles in ontology research. Authors were more from North America, Europe, and East Asia. The USA took the lead, while China grew fastest. Four major categories of frequently used keywords were identified: applications in Semantic Web, applications in bioinformatics, philosophy theories, and common supporting technology. Semantic Web research played a core role, and gene ontology study was well-developed. The study focus of ontology has shifted from philosophy to information science.

This is the first study to quantify global research patterns and trends in ontology, which might provide a potential guide for the future research. The new index provides an alternative way to evaluate the multidisciplinary influence of researchers.

There is still little support for the consumer decision‐making process on the web, especially when prices are not the primary property of a product. Reasons for that are complex product specifications as well as often volitional weak interoperability between e‐commerce sites. This paper aims to address this issue.

The semantic web is supposed to make product information more interoperable between different sites. Additionally, some products with limited time frames of availability, like real estates or second‐hand cars, require periodical searches over several days, weeks, or even months. For those kinds of products existing systems cannot be applied. Instant information about new offers on the market is therefore crucial. Wireless access to the web enables services to become instantaneous and to provide up‐to‐date information to users.

This paper presents a framework which is based on multivariate product comparison allowing users to delegate search requests to an agent. The success of the agent depends heavily on the matching algorithm. Fuzzy utility functions and the analytical hierarchy process are a very feasible combination for the scoring of offers.

The proposed system supports users finding products on the web matching specific user preferences and instantly informs them when new items become available on the virtual market. As a specific use case the framework is being applied to the real estate sector, because especially for this sector several shortcomings of the current support have been identified.

The purpose of this paper is to improve the conceptual-based search by incorporating structural ontological information such as concepts and relations. Generally, Semantic-based information retrieval aims to identify relevant information based on the meanings of the query terms or on the context of the terms and the performance of semantic information retrieval is carried out through standard measures-precision and recall. Higher precision leads to the (meaningful) relevant documents obtained and lower recall leads to the less coverage of the concepts.

In this paper, the authors enhance the existing ontology-based indexing proposed by Kohler et al., by incorporating sibling information to the index. The index designed by Kohler et al., contains only super and sub-concepts from the ontology. In addition, in our approach, we focus on two tasks; query expansion and ranking of the expanded queries, to improve the efficiency of the ontology-based search. The aforementioned tasks make use of ontological concepts, and relations existing between those concepts so as to obtain semantically more relevant search results for a given query.

The proposed ontology-based indexing technique is investigated by analysing the coverage of concepts that are being populated in the index. Here, we introduce a new measure called index enhancement measure, to estimate the coverage of ontological concepts being indexed. We have evaluated the ontology-based search for the tourism domain with the tourism documents and tourism-specific ontology. The comparison of search results based on the use of ontology “with and without query expansion” is examined to estimate the efficiency of the proposed query expansion task. The ranking is compared with the ORank system to evaluate the performance of our ontology-based search. From these analyses, the ontology-based search results shows better recall when compared to the other concept-based search systems. The mean average precision of the ontology-based search is found to be 0.79 and the recall is found to be 0.65, the ORank system has the mean average precision of 0.62 and the recall is found to be 0.51, while the concept-based search has the mean average precision of 0.56 and the recall is found to be 0.42.

When the concept is not present in the domain-specific ontology, the concept cannot be indexed. When the given query term is not available in the ontology then the term-based results are retrieved.

In addition to super and sub-concepts, we incorporate the concepts present in same level (siblings) to the ontological index. The structural information from the ontology is determined for the query expansion. The ranking of the documents depends on the type of the query (single concept query, multiple concept queries and concept with relation queries) and the ontological relations that exists in the query and the documents. With this ontological structural information, the search results showed us better coverage of concepts with respect to the query.

This paper aims to reorganize the relevant information of Chinese ancient architectures with the use of Semantic Web technologies and thus facilitate its deep discovery and usage.

This paper proposes an ontology model for Chinese ancient architectures based on architectural narratives theory. To verify the availability of the ancient architecture ontology, we designed and implemented three experiments, including semantic retrieval based on SPARQL query, semantic reasoning with the use of Jena reasoner and visual analysis based on the Chinese Online Digital Humanities Resources Platform.

The proposed ontology provided a solution for the semantic annotation of the unstructured information of Chinese ancient architectures. On this basis, deep knowledge services such as semantic retrieval, semantic reasoning and visual analysis can be provided.

The proposed semantic model of ancient architectures can effectively improve the organization and access quality of the semantic content of Chinese ancient architectures.

This paper focuses on the semantic modelling for the unstructured information of Chinese ancient architectures to semantically describe the related entities (e.g. persons, events, places and times) and uncover their relationships, and thus it made contribution to the deep semantic annotations on ancient architectures.

Many organizations in the local community environment use and produce geo‐spatial data, so the need for integration of geo‐data is increasing rapidly. Different user groups have different views of the world and information is available in a heterogeneous format. This paper seeks to discuss the need for interoperability in local communities taking Chittagong city of Bangladesh as an example.

These communities use geo‐spatial data in their own format. This results in semantic conflicts, arising when there is a need for integration of the geo‐spatial data. Consequently, the interaction among the aforesaid organizations in terms of data is difficult to achieve and therefore, it is difficult to share the benefit of the recently evolving Information Technology. Taking the above viewpoint into account, this paper presents a framework to address such semantic data conflicts, considered as an issue of interoperability, using ontology.

This paper presented an ontology‐based architecture which can be used in resolving semantic conflicts, enabling the tackling of the interoperability issue, faced by the various local communities. The proposed architecture will reduce the computational time significantly because it does not require processing each query every timeResearch limitations/implications – The architecture presented needs to test with real data in the near future.

In order to share the geo‐data available in different formats, there is a need for developing a global community, consisting of an integrator, global schema and common ontology.

It has been shown that the architecture allows the sharing of geo‐data by resolving geo‐semantic conflicts of the local communities. This will in turn play an important role in addressing the interoperability problem, faced by these communities.