Modeling Recipes for Online Search

Chatterjee, Usashi; Giunchiglia, Fausto; Madalli, Devika P.; Maltese, Vincenzo

doi:10.1007/978-3-319-48472-3_37

Cited by 4 publications

(8 citation statements)

References 10 publications

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“…We inferred what is needed from the mockups of the digital services. This is consistent with modeling methodologies where mockups play the role of competency questions [18,19]. This is a preprint of an article whose final and definitive form has been published in the Cataloging & Classification Volume 56, 2018 -Issue 7 -https://doi.org/10.1080/01639374.2018.1504847…”

Section: Step 2: Setting Up the Data Modelsupporting

confidence: 76%

Digital Transformation Challenges for Universities: Ensuring Information Consistency Across Digital Services

Maltese

2018

Cataloging & Classification Quarterly

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Universities struggle to offer complete, up-to-date and consistent information about their key assets to their numerous users across various digital services and communication channels. Key assets include people, papers, books, dissertations, patents, courses and research projects. The main difficulty stands in the intrinsic data fragmentation and data diversity: data about the key assets is scattered across multiple information silos, data is often duplicated and difficult to correlate due to the diversity in format, metadata, conventions and terminology used. We illustrate how this difficulty can be tackled and describe the work carried out at the University of Trento in Italy.

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Section: Step 2: Setting Up the Data Modelsupporting

confidence: 76%

Digital Transformation Challenges for Universities: Ensuring Information Consistency Across Digital Services

Maltese

2018

Cataloging & Classification Quarterly

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“…In this step, the data model is extended incrementally with entity types and properties that are necessary to support the new service. [12] presents a methodology that can be followed to design the data model based on a set of user queries.…”

Section: The Methodologymentioning

confidence: 99%

“…the University of Florida 9 . Among the top universities worldwide, we found two notable cases, namely, the HKU Scholars Hub 10 , based on a custom solution, and the John Hopkins portal 11 , based on Elsevier Pure 12 .…”

Section: Introductionmentioning

confidence: 99%

An Architecture and a Methodology Enabling Interoperability within and across Universities

Giunchiglia

Maltese

Ganbold

et al. 2022

2022 IEEE International Conference on Knowledge Graph (ICKG)

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We propose a general methodology and an infrastructure which allows to achieve interoperability within the same university and across universities. The former goal is achieved by incrementally defining and building a knowledge graph (KG) using data coming from multiple heterogeneous databases. Interoperability across universities is achieved by having a reference KG schema that each university can adapt to the local needs, but keeping track of the changes, and by natively supporting multilinguality. We achieve this latter requirement by exploiting a multilingual lexical resource containing more than one thousand languages and by seamlessly translating across the schemas and also (to some extent) across the data written in the local languages. The effectiveness of the proposed approach is proven by the services developed in the context of two different projects conducted in two universities in Italy and Mongolia.

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“…Every step of interpreting a query needs to consider the context [52]. A knowledge model [11] is used for query understanding, query analysis and query representation. In an information system, good output depends upon good knowledge representation [53], as representation of knowledge enables the establishment of relationships between real-world entities [44].…”

Section: Methodsmentioning

confidence: 99%

Context-based understanding of food-related queries using a culinary knowledge model

Chatterjee

2021

Journal of Information Science

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Dietary practices are governed by a mix of ethnographic aspects, such as social, cultural and environmental factors. These aspects need to be taken into consideration during an analysis of food-related queries. Queries are usually ambiguous. It is essential to understand, analyse and refine the queries for better search and retrieval. The work is focused on identifying the explicit, implicit and hidden facets of a query, taking into consideration the context – culinary domain. This article proposes a technique for query understanding, analysis and refinement based on a domain specific knowledge model. Queries are conceptualised by mapping the query term to concepts defined in the model. This allows an understanding of the semantic point of view of a query and an ability to determine the meaning of its terms and their interrelatedness. The knowledge model acts as a backbone providing the context for query understanding, analysis and refinement and outperforms other models, such as Schema.org , BBC Food Ontology and Recipe Ontology.

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Modeling Recipes for Online Search

Cited by 4 publications

References 10 publications

Digital Transformation Challenges for Universities: Ensuring Information Consistency Across Digital Services

Digital Transformation Challenges for Universities: Ensuring Information Consistency Across Digital Services

An Architecture and a Methodology Enabling Interoperability within and across Universities

Context-based understanding of food-related queries using a culinary knowledge model

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