The onset of Web 2.0 has given the freedom of tagging to the users. The popularization of social networking and the expansion of the smartphone market in the past decade has led to an increase of data being accumulated on the social media platforms, particularly images and videos. The exponential and ever increasing data have made information retrieval cumbersome, especially for the social network users, and this has turned out to be a huge challenge in the evolution of algorithms and technologies. In this paper, we present a novel framework and techniques for retrieving user’s multimedia content like images from the user’s profile using the context of the image/media file. We apply the Logical Itemset mining on the image Metadata consisting of the textual data (Hashtags, Caption, Date and Time) associated with the images. Through this work, we intend to bridge the semantic gap between the images and the data representation that the user associated with them. Our framework also addresses the paraphrase problem of variation in words (synonyms) used to describe a context of a media file. To evaluate the applicability of our framework, we performed tests on large Instagram image dataset extracted from various user profiles containing monolingual metadata, which show promising results for real-time applications. Furthermore, we compare and evaluate our framework with another context-based image retrieval framework, Krumbs.
Multimedia Tools and Applications – Springer Journals
Published: Jul 5, 2017
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera