Image recommendation is an important feature of search engine, as tremendous amount of images are available online. It is necessary to retrieve relevant images to meet the user's requirement. In this paper, we present an algorithm image recommendation with absorbing Markov chain (IRAbMC) to retrieve relevant images for a user's input query. Images are ranked by calculating keyword relevance probability between annotated keywords from log and keywords of user input query. Keyword relevance is computed using absorbing Markov chain. Images are reranked using image visual features. Experimental results show that the IRAbMC algorithm outperforms Markovian semantic indexing (MSI) method with improved relevance score of retrieved ranked images.

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Query recommendation is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of recommendation like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the recommendations. If we model the data into various kinds of graphs then we can build a general method for any recommendation. In this paper, we have proposed a general method for query recommendation by combining two graphs: 1) query click graph which captures the relationship between queries frequently clicked on common URLs and 2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users' need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product recommendation.

Abstract. Query suggestion is an important feature of the search engine with the explosive and diverse growth of web contents. Different kind of suggestions like query, image, movies, music and book etc. are used every day. Various types of data sources are used for the suggestions. If we model the data into various kinds of graphs then we can build a general method for any suggestions. In this paper, we have proposed a general method for query suggestion by combining two graphs: (1) query click graph which captures the relationship between queries frequently clicked on common URLs and (2) query text similarity graph which finds the similarity between two queries using Jaccard similarity. The proposed method provides literally as well as semantically relevant queries for users' need. Simulation results show that the proposed algorithm outperforms heat diffusion method by providing more number of relevant queries. It can be used for recommendation tasks like query, image, and product suggestion.

Cymbopogon flexuosus (lemongrass) is one of the potential herbaceous sources for the extraction of silica. Silica plays a vital role in formation of bone and its maintenance by improving the quality of the bone matrix and facilitating bone mineralization. This work presents the extraction of silica nanoparticles from different parts of lemongrass such as root, stem and leaf. IR spectra of all the three extracts confirmed the presence of siloxane and silanol linkage. The SEM analysis revealed the SiNPs from root, stem and leaves to be aggregates of tubular, fibrous and spherical structures, respectively. Significant differences were observed in elemental composition of SiNPs as determined by EDAX. Optimization of the acid leaching process further enhanced the yield by around 30% from leaves. EDAX revealed significant differences in the elemental composition. The DLS histogram showed a size distribution of 62.4 nm validating Zetasizer evaluation having PdI of 0.127. The work also reports the screening of drugs through in silico approach wherein the drug risedronate showed ideal parameters satisfying the Lipinski's rule of 5. Further, the cytotoxicity of SiNPs and SiNPs with risedronate (drug) was tested on HUVEC and Saos-2 cell lines. The SiNPs showed lesser IC 50 value in comparison with risedronate and SiNPs with risedronate tested on both the cell lines. LDH assay elaborated prominent cell leakage by risedronateanchored SiNPs which is found significant in comparison with bare SiNPs. Treatment of the osteoporotic cells with risedronate/silica blend (1:1000) revealed efficient deposition of calcium and drug in the cells as determined by microscopic observations. Drug release studies of SiNPs with risedronate were performed. FTIR indicated the presence of siloxane (Si-O-Si) and silanol (Si-OH) functional groups. In vitro study of different ratios of risedronate with silica on Saos-2 cell lines was performed to determine the mineralization potential of the combinatorial drug. It was found that the cells incubated with 0.6 mg/ml and 0.8 mg/ml of risedronate with silica showed efficient deposition of calcium inside the cells. The wild variety of Cymbopogon flexuosus could be a potential source for the extraction of SiNPs, which finds much use in biomedical applications.

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