scholarly journals Introduction to the Special Issue on Image-Based Information Retrieval from the Web

2019 ◽  
Vol 5 (7) ◽  
pp. 62
Author(s):  
Phivos Mylonas ◽  
Evaggelos Spyrou
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Multimedia Content ◽  
Special Issue ◽  
Digital Multimedia ◽  
The Web

In recent years, following the tremendous growth of the Web, extremely large amounts of digital multimedia content are being produced every day and are shared online mainly through several newly emerged channels, such as social networks [...]

scholarly journals Special Issue on Searching and Mining the Web and Social Networks

2014 ◽  
Vol 10 (3-4) ◽  
pp. 219-221
Author(s):  
Nelly Litvak ◽  
Sebastiano Vigna
Keyword(s):  
Social Networks ◽  
Special Issue ◽  
The Web

Web Information Retrieval

2011 ◽  
pp. 218-252 ◽  
Author(s):  
Guillaume Cabanac ◽  
Max Chevalier ◽  
Claude Chrisment ◽  
Christine Julien ◽  
Chantal Soulé-Dupuy ◽  
...  
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Search Engine ◽  
Information Search ◽  
Information Needs ◽  
Information Source ◽  
Web Information Retrieval ◽  
Web Information ◽  
The Social ◽  
The Web

Nowadays, the Web has become the most queried information source. To solve their information needs, individuals can use different types of tools or services like a search engine, for instance. Due to the high amount of information and the diversity of human factors, searching for information requires patience, perseverance, and sometimes luck. To help individuals during this task, search assistants feature adaptive techniques aiming at personalizing retrieved information. Moreover, thanks to the “new Web” (the Web 2.0), personal search assistants are evolving, using social techniques (social networks, sharing-based methods). Let us enter into the Social Web, where everyone collaborates with others in providing their experience, their expertise. This chapter introduces search assistants and underlines their evolution toward Social Information Search Assistants.

A distributional semantics-based information retrieval framework for online social networks

2021 ◽  
pp. 1-11
Author(s):  
V.S. Anoop ◽  
P. Deepak ◽  
S. Asharaf
Keyword(s):  
Social Networks ◽  
Information Retrieval ◽  
Online Social Networks ◽  
Latent Dirichlet Allocation ◽  
Relevant Information ◽  
Distributional Semantics ◽  
Scalable Algorithms ◽  
Mobile Platforms ◽  
Cancer Support ◽  
Efficient Extraction

Online social networks are considered to be one of the most disruptive platforms where people communicate with each other on any topic ranging from funny cat videos to cancer support. The widespread diffusion of mobile platforms such as smart-phones causes the number of messages shared in such platforms to grow heavily, thus more intelligent and scalable algorithms are needed for efficient extraction of useful information. This paper proposes a method for retrieving relevant information from social network messages using a distributional semantics-based framework powered by topic modeling. The proposed framework combines the Latent Dirichlet Allocation and distributional representation of phrases (Phrase2Vec) for effective information retrieval from online social networks. Extensive and systematic experiments on messages collected from Twitter (tweets) show this approach outperforms some state-of-the-art approaches in terms of precision and accuracy and better information retrieval is possible using the proposed method.

A method of query expansion based on topic models and user profile for search in folksonomy

2021 ◽  
pp. 1-11
Author(s):  
Zhinan Gou ◽  
Yan Li
Keyword(s):  
Information Retrieval ◽  
Query Expansion ◽  
Information Overload ◽  
Topic Model ◽  
User Profile ◽  
Expansion Method ◽  
Collaborative Tagging ◽  
Search Query ◽  
Tagging System ◽  
The Web

With the development of the web 2.0 communities, information retrieval has been widely applied based on the collaborative tagging system. However, a user issues a query that is often a brief query with only one or two keywords, which leads to a series of problems like inaccurate query words, information overload and information disorientation. The query expansion addresses this issue by reformulating each search query with additional words. By analyzing the limitation of existing query expansion methods in folksonomy, this paper proposes a novel query expansion method, based on user profile and topic model, for search in folksonomy. In detail, topic model is constructed by variational antoencoder with Word2Vec firstly. Then, query expansion is conducted by user profile and topic model. Finally, the proposed method is evaluated by a real dataset. Evaluation results show that the proposed method outperforms the baseline methods.

The Web and social networks

Computer ◽  
2002 ◽  
Vol 35 (11) ◽  
pp. 32-36 ◽  
Author(s):  
R. Kumar ◽  
P. Ragbavan ◽  
S. Rajagopalan ◽  
A. Tomkins
Keyword(s):  
Social Networks ◽  
The Web

Open System for Indexing and Retrieving Multimedia Information

2013 ◽  
Author(s):  
Hanene Maghrebi ◽  
Amos David
Keyword(s):  
Information Retrieval ◽  
Multimedia Information ◽  
Open System ◽  
Large Volume ◽  
Retrieval System ◽  
Main Idea ◽  
Relevant Information ◽  
Information Retrieval System ◽  
Multimedia Content ◽  
Nous Proposons

Managing the increasing growth of multimedia content still poses some problems. The challenge is to propose relevant information to the users among the large volume of information available. The main idea that drives our approach is to provide an open information retrieval system, which can adapt its results to several…La gestion de l’information multimédia soulève encore quelques problèmes. Le défi est de pouvoir proposer à l’utilisateur des informations pertinentes parmi la quantité d’information qui ne cesse de s’accroître. Dans cette lignée, nous proposons un système ouvert de recherche d’information capable d’adapter ses résultats aux différents… 

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