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FoodWiki: Ontology-Driven Mobile Safe Food Consumption System.

Çelik D - ScientificWorldJournal (2015)

Bottom Line: An ontology-driven safe food consumption mobile system is considered.Next-generation smart knowledgebase systems will not only include traditional syntactic-based search, which limits the utility of the search results, but will also provide semantics for rich searching.In this paper, performance of concept matching of food ingredients is semantic-based, meaning that it runs its own semantic based rule set to infer meaningful results through the proposed Ontology-Driven Mobile Safe Food Consumption System (FoodWiki).

View Article: PubMed Central - PubMed

Affiliation: Computer Engineering Department, Istanbul Aydin University, 34295 Istanbul, Turkey.

ABSTRACT
An ontology-driven safe food consumption mobile system is considered. Over 3,000 compounds are being added to processed food, with numerous effects on the food: to add color, stabilize, texturize, preserve, sweeten, thicken, add flavor, soften, emulsify, and so forth. According to World Health Organization, governments have lately focused on legislation to reduce such ingredients or compounds in manufactured foods as they may have side effects causing health risks such as heart disease, cancer, diabetes, allergens, and obesity. By supervising what and how much to eat as well as what not to eat, we can maximize a patient's life quality through avoidance of unhealthy ingredients. Smart e-health systems with powerful knowledge bases can provide suggestions of appropriate foods to individuals. Next-generation smart knowledgebase systems will not only include traditional syntactic-based search, which limits the utility of the search results, but will also provide semantics for rich searching. In this paper, performance of concept matching of food ingredients is semantic-based, meaning that it runs its own semantic based rule set to infer meaningful results through the proposed Ontology-Driven Mobile Safe Food Consumption System (FoodWiki).

No MeSH data available.


Related in: MedlinePlus

Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic Acid) are three subconcepts of the Ascorbic Acid concept, and each link has 0.333 weight value.
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fig5: Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic Acid) are three subconcepts of the Ascorbic Acid concept, and each link has 0.333 weight value.

Mentions: The above equation considers two lists C = {C1, C2,…, Cm} and P = {P1, P2,…, Pn} of the C and P. In (3), distance(Ci, Pj) shows the number of concepts (levels) between any two focused concepts, Ci and Pj, in the ontology. Assume that the Ascorbic Acid concept has three subconcepts in the ontology, such as Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic acid) (Figure 5). Also assume that the semantically enhanced consumer intolerance list (C) contains the D-Isoascorbic Acid (Erythorbic Acid) concept since the consumer may have some skin problems when consuming it. In addition, assume that the consumer may choose a product on the market shelves that contains Ascorbic Acid. Therefore, the value of the dweight(AscorbicAcid, Dehydroascorbic Acid) will be 1/3, that is, rounded as 0.333.


FoodWiki: Ontology-Driven Mobile Safe Food Consumption System.

Çelik D - ScientificWorldJournal (2015)

Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic Acid) are three subconcepts of the Ascorbic Acid concept, and each link has 0.333 weight value.
© Copyright Policy - open-access
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4496660&req=5

fig5: Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic Acid) are three subconcepts of the Ascorbic Acid concept, and each link has 0.333 weight value.
Mentions: The above equation considers two lists C = {C1, C2,…, Cm} and P = {P1, P2,…, Pn} of the C and P. In (3), distance(Ci, Pj) shows the number of concepts (levels) between any two focused concepts, Ci and Pj, in the ontology. Assume that the Ascorbic Acid concept has three subconcepts in the ontology, such as Ester C, Ascorbyl Palmitate (Vitamin C Ester), and D-Isoascorbic Acid (Erythorbic acid) (Figure 5). Also assume that the semantically enhanced consumer intolerance list (C) contains the D-Isoascorbic Acid (Erythorbic Acid) concept since the consumer may have some skin problems when consuming it. In addition, assume that the consumer may choose a product on the market shelves that contains Ascorbic Acid. Therefore, the value of the dweight(AscorbicAcid, Dehydroascorbic Acid) will be 1/3, that is, rounded as 0.333.

Bottom Line: An ontology-driven safe food consumption mobile system is considered.Next-generation smart knowledgebase systems will not only include traditional syntactic-based search, which limits the utility of the search results, but will also provide semantics for rich searching.In this paper, performance of concept matching of food ingredients is semantic-based, meaning that it runs its own semantic based rule set to infer meaningful results through the proposed Ontology-Driven Mobile Safe Food Consumption System (FoodWiki).

View Article: PubMed Central - PubMed

Affiliation: Computer Engineering Department, Istanbul Aydin University, 34295 Istanbul, Turkey.

ABSTRACT
An ontology-driven safe food consumption mobile system is considered. Over 3,000 compounds are being added to processed food, with numerous effects on the food: to add color, stabilize, texturize, preserve, sweeten, thicken, add flavor, soften, emulsify, and so forth. According to World Health Organization, governments have lately focused on legislation to reduce such ingredients or compounds in manufactured foods as they may have side effects causing health risks such as heart disease, cancer, diabetes, allergens, and obesity. By supervising what and how much to eat as well as what not to eat, we can maximize a patient's life quality through avoidance of unhealthy ingredients. Smart e-health systems with powerful knowledge bases can provide suggestions of appropriate foods to individuals. Next-generation smart knowledgebase systems will not only include traditional syntactic-based search, which limits the utility of the search results, but will also provide semantics for rich searching. In this paper, performance of concept matching of food ingredients is semantic-based, meaning that it runs its own semantic based rule set to infer meaningful results through the proposed Ontology-Driven Mobile Safe Food Consumption System (FoodWiki).

No MeSH data available.


Related in: MedlinePlus