An architecture for non-linear discovery of aggregated multimedia document web search results

Abstract

The recent proliferation of multimedia information on the web enhances user information need from simple textual lookup to multi-modal exploration activities. The current search engines act as major gateways to access the immense amount of multimedia data. However, access to the multimedia content is provided by aggregating disjoint multimedia search verticals. The aggregation of the multimedia search results cannot consider relationships in them and are partially blended. Additionally, the search results’ presentation is via linear lists, which cannot support the users’ non-linear navigation patterns to explore the multimedia search results. Contrarily, users’ are demanding more services from search engines. It includes adequate access to navigate, explore, and discover multimedia information. Our discovery approach allow users to explore and discover multimedia information by semantically aggregating disjoint verticals using sentence embeddings and transforming snippets into conceptually similar multimedia document groups. The proposed aggregation approach retains the relationship in the retrieved multimedia search results. A non-linear graph is instantiated to augment the users’ non-linear information navigation and exploration patterns, which leads to discovering new and interesting search results at various aggregated granularity levels. Our method’s empirical evaluation results achieve 99% accuracy in the aggregation of disjoint search results at different aggregated search granularity levels. Our approach provides a standard baseline for the exploration of multimedia aggregation search results.

An SUI-based approach to explore visual search results cluster-graphs

“…In advanced exploration mechanisms, the non-linear representations like graphs and trees connect search results via non-linear relationships [11,12,28]. In non-linear representations, the nodes represent visual contents connected via different types of relationships as edges [5].…”

“…Images engagement in web search and users' exploration activities is higher than contents belonging to other media formats [10]. The web search engines provide retrieval mechanisms to satisfy the visual information needs [11]. The users may express their information needs as textual query terms and interact with the visual contents [12].…”

“…However, the increase in imaginary information and retrieval via web search engines makes exploration services challenging [9]. The information needs are profoundly affected triad of visual retrieval, which requires intriguing advance and comprehensive lookup, exploration, and discovery mechanisms in web search [11,13,14].…”

I-Cubid: a nonlinear cubic graph-based approach to visualize and in-depth browse Flickr image results

“…Similarly, users are becoming interested in multimodal interaction ( Rashid, 2017 ). Various approaches have been devised to connect an image and video content based on similarity ( Rashid, 2017 ; Rashid, Saleem & Ahmed, 2021 ; Khan et al, 2021 ). A few of the state-of-the-art image search engines, such as Pexels ( http://pexels.com/ ), Morguefile ( https://morguefile.com/ ), Vecteezy ( https://www.vecteezy.com/ ), etc.…”

Sampling Fingerprints From Multimedia Content Resource Clusters

“…The techniques to access vast multimedia resources are becoming integral to user interaction and exploration scenarios [15], [16]. The exploration scenarios require fingerprint sampling from multimedia resources in the user's exploration activities [17]. Fingerprinting is about extracting information subsets from a divergent information resource that may represent a concept as a whole [18].…”