Evaluation of Semantic Similarity Using Vector Space Model Based on Textual Corpus

Entities interacting on the web establish their identity by creating virtual personas. These entities, or agents, can be human users or software-based. This research models identity using the Entity-Persona Model, a semantically annotated social network inferred from the persistent traces of interaction between personas on the web. A Persona Mapping Algorithm is proposed which compares the local views of personas in their social network referred to as their Virtual Signatures, for structural and semantic similarity. The semantics of the Entity-Persona Model are modeled by a vector space model of the text associated with the personas in the network, which allows comparison of their Virtual Signatures. This enables all the publicly accessible personas of an entity to be identified on the scale of the web. This research enables an agent to identify a single entity using multiple personas on different networks, provided that multiple personas exhibit characteristic behavior. The agent is able to increase the trustworthiness of on-line interactions by establishing the identity of entities operating under multiple personas. Consequently, reputation measures based on on-line interactions with multiple personas can be aggregated and resolved to the true singular identity.

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Modeling Virtual Footprints

Theoretical and Practical Frameworks for Agent-Based Systems ◽

10.4018/978-1-4666-1565-6.ch007 ◽

2012 ◽

pp. 96-113

Author(s):

Rajiv Kadaba ◽

Suratna Budalakoti ◽

David DeAngelis ◽

K. Suzanne Barber

Keyword(s):

Social Network ◽

Vector Space ◽

Semantic Similarity ◽

Vector Space Model ◽

Mapping Algorithm ◽

Space Model ◽

Single Entity ◽

Characteristic Behavior ◽

On Line ◽

The Web

Entities interacting on the web establish their identity by creating virtual personas. These entities, or agents, can be human users or software-based. This research models identity using the Entity-Persona Model, a semantically annotated social network inferred from the persistent traces of interaction between personas on the web. A Persona Mapping Algorithm is proposed which compares the local views of personas in their social network referred to as their Virtual Signatures, for structural and semantic similarity. The semantics of the Entity-Persona Model are modeled by a vector space model of the text associated with the personas in the network, which allows comparison of their Virtual Signatures. This enables all the publicly accessible personas of an entity to be identified on the scale of the web. This research enables an agent to identify a single entity using multiple personas on different networks, provided that multiple personas exhibit characteristic behavior. The agent is able to increase the trustworthiness of on-line interactions by establishing the identity of entities operating under multiple personas. Consequently, reputation measures based on on-line interactions with multiple personas can be aggregated and resolved to the true singular identity.

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Text Document Categorization using Enhanced Sentence Vector Space Model and Bi-Gram Text Representation Model Based on Novel Fusion Techniques

10.7176/nmmc/93-03 ◽

2020 ◽

Keyword(s):

Vector Space ◽

Vector Space Model ◽

Text Representation ◽

Space Model ◽

Model Based ◽

Text Document ◽

Representation Model ◽

Document Categorization

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Information Retrieval System in the Bible

CogITo Smart Journal ◽

10.31154/cogito.v7i1.300.111-120 ◽

2021 ◽

Vol 7 (1) ◽

pp. 111

Author(s):

Apriandy Angdresey ◽

Miguel Angelo Lamongi ◽

Rinaldi Munir

Keyword(s):

Information Retrieval ◽

Vector Space ◽

Retrieval System ◽

Vector Space Model ◽

Information Retrieval System ◽

Space Model ◽

Model Based ◽

The Bible

Information retrieval is used to search for relevant documents so that they can be obtained quickly and precisely. There are many Christians who want to study the gospel. However, often experience problems in finding the Gospel verse and topics dealing with the need to search by the user. Therefore, have to search individually, each verse in the four Gospels to find the topic or verse that the user wants to find out. In this study, the authors used the Bible verses in the Gospels as documents, so that these verses could be searched for the level of relevance or similarity to the entered keywords. Furthermore, to determine the level of relevance between documents and keywords is calculated using the Vector Space Model. Based on the application that has been successfully built, the application can be show 10 documents related to the keywords that are searched and sorted from the most relevant, with the highest similarity value, namely 78.65%.Keywords - Information Retrieval, Vector Space Model, Bible.

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