Noemi Mauro

Exploration of cultural heritage information via textual search queries

Searching information in a Geographical Information System (GIS) usually imposes that users explore precompiled category catalogs and select the types of information they are looking for. Unfortunately, that approach is challenging because it forces people to adhere to a conceptualization of the information space that might be different from their own. In order to address this issue, we propose to support textual search as the basic interaction model, exploiting linguistic information, together with category exploration, for query interpretation and expansion. This paper describes our model and its adoption in the OnToMap Participatory GIS.

OnToMap: Semantic Community Maps for Knowledge Sharing

We present the information retrieval model adopted in the OnToMap Participatory GIS. The model addresses the limitations of keyword-based and category-based search by semantically interpreting the information needs specified in free-text search queries. The model is based on an ontological representation of linguistic and encyclopaedic knowledge, which makes it possible to exploit terms and synonyms occurring in the definitions of concepts to flexibly match the users and systems terminologies. This feature enables users to query the application using their own vocabulary.

Semantic Interpretation of Search Queries for Personalization

This demo paper describes the semantic query interpretation model adopted in the OnToMap Participatory GIS and presents its benefits to information retrieval and personalized information presentation.

Concept-aware geographic information retrieval

Textual queries are largely employed in information retrieval to let users specify search goals in a natural way. However, differences in user and system terminologies can challenge the identification of the users information needs, and thus the generation of relevant results. We argue that the explicit management of ontological knowledge, and of the meaning of concepts (by integrating linguistic and encyclopaedic knowledge in the system ontology), can improve the analysis of search queries, because it enables a flexible identification of the topics the user is searching for, regardless of the adopted vocabulary. This paper proposes an information retrieval support model based on semantic concept identification. Starting from the recognition of the ontology concepts that the search query refers to, this model exploits the qualifiers specified in the query to select information items on the basis of possibly fine-grained features. Moreover, it supports query expansion and reformulation by suggesting the exploration of semantically similar concepts, as well as of concepts related to those referred in the query through thematic relations. A test on a data-set collected using the OnToMap Participatory GIS has shown that this approach provides accurate results.

Map-based visualization of 2D/3D spatial data via stylization and tuning of information emphasis

In Geographical Information search, map visualization can challenge the user because results can consist of a large set of heterogeneous items, increasing visual complexity. We propose a novel visualization model to address this issue. Our model represents results as markers, or as geometric objects, on 2D/3D layers, using stylized and highly colored shapes to enhance their visibility. Moreover, the model supports interactive information filtering in the map by enabling the user to focus on different data categories, using transparency sliders to tune the opacity, and thus the emphasis, of the corresponding data items. A test with users provided positive results concerning the efficacy of the model.

Thematic Maps for Geographical Information Search

The exploration of cultural heritage information is challenged by the fact that most data provided by online resources is fragmented and it is repository or application-centered. In order to address this issue, a data integration approach should be adopted, that makes it possible to generate custom views, focused on the users information needs, but easily extensible to support the inspection of topically related contents. In this paper, we present a model supporting the management of thematic maps for information exploration, and their integration with query expansion during the interaction with the user. Our model is based on: (i) an ontological domain knowledge representation for describing the meaning of concepts and their semantic relations; (ii) a semantic interpretation model for identifying the concepts referenced in the users queries. We are experimenting our model in the OnToMap Participatory GIS, which manages interactive community maps for information sharing and participatory decision-making.

Supporting Knowledge Sharing and Learning via Semantic Geographical Maps

Map-based applications are a good starting point for helping teachers in the preparation of learning material and students in their researches in social sciences. However, they offer basic information filtering support to the generation of dynamic maps. In this paper, we investigate the adoption of semantic knowledge representation and cooperative work approaches for managing thematic maps in group-based learning activities. Moreover, we present a possible solution, based on the OnToMap Participatory GIS, which uses an ontological representation of geographical information to support multi-faceted information retrieval, crowdsourcing, and map creation.

Transparency-based information filtering on 2D/3D geographical maps

The presentation of search results in GIS can expose the user to cluttered geographical maps, challenging the identification of relevant information. In order to address this issue, we propose a visualization model supporting interactive information filtering on 2D/3D maps. Our model is based on the introduction of transparency sliders that enable the user to tune the opacity, and thus the emphasis, of data categories in the map. In this way, he or she can focus the maps on the most relevant types of information for the task to be performed. A test with users provided positive results concerning the efficacy of our model.

Intelligent and Personalized Community Maps

My PhD project focuses on Participatory GIS (PGIS). In the project I analyze two methodologies to offer personalized search results in community maps and a natural interaction with the system. The first consists of automatically gathering the terms according to which the users express their information needs, in order to enrich the domain conceptualization of a PGIS, giving common definitions for places. The second concerns the creation of ontology-based user models that reflect the interests, lexicon and modality of expression adopted by each person, mapped to the domain ontology adopted by the PGIS. In the project I also analyze how these techniques may be jointly used during the query expansion process to retrieve more accurate and relevant search results.

Personalization in Geographical Information Search.

My PhD project focuses on the personalization of Participatory GIS (PGIS). In the project I analyze two methodologies to offer personalized search results in community maps and a natural interaction with the system. The first consists of automatically gathering the users interests at a concept level in order to generate clusters of concepts useful for the presentation of thematic maps. This is done by creating ontology-based user models mapped to the domain ontology adopted by the PGIS. The second concerns the creation of content-based user models useful for filtering the items belonging to each concept in a multifaceted way: the goal is that of reducing and adapting the information space presented in the map. In the project I also analyze how these techniques may be jointly used during the query expansion process to retrieve more accurate and relevant search results.