Fuzzy Clustering Based Ad Recommendation for TV Programs

Advertisements(Ads) are the main revenue earner for Television (TV) broadcasters. As TV reaches a large audience, it acts as the best media for advertisements of products and services. With the emergence of digital TV, it is important for the broadcasters to provide an intelligent service according to the various dimensions like program features, ad features, viewers’ interest and sponsors’ preference. We present an automatic ad recommendation algorithm that selects a set of ads by considering these dimensions and semantically match them with programs. Features of the ad video are captured interms of annotations and they are grouped into number of predefined semantic categories by using a categorization technique. Fuzzy categorical data clustering technique is applied on categorized data for selecting better suited ads for a particular program. Since the same ad can be recommended for more than one program depending upon multiple parameters, fuzzy clustering acts as the best suited method for ad recommendation. The relative fuzzy score called “degree of membership” calculated for each ad indicates the membership of a particular ad to different program clusters. Subjective evaluation of the algorithm is done by 10 different people and rated with a high success score.

Comparative measurements of HV impulses to evaluate different sets of response parameters

Results are reported of comparative measurements made in 14 HV (high-voltage) laboratories in ten different countries. The theory of the proposed methods of characterizing the dynamic behavior is given, and the parameters to be used are discussed. Comparative measurements made using 95 systems based on 53 dividers are analyzed. This analysis shows that many of the system now in use, even though they fulfil the basic response requirements of the standards, do not meet the accuracy requirements. Because no transfer measurements were made between laboratories, there is no way to detect similar errors in both the system under test and the reference system. Hence, the situation may be worse than reported. This has led to the recommendation that comparative measurements should be the main route for quantifying industrial impulse measuring systems

Mining sentiments from songs using latent dirichlet allocation

Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.

Definition of the halogen bond (IUPAC Recommendations 2013)

This recommendation proposes a definition for the term ``halogen bond'', which designates a specific subset of the inter- and intramolecular interactions involving a halogen atom in a molecular entity.

Fe as Hydrogen/Halogen Bond Acceptor in Square Pyramidal Fe(CO)(5)

Hydrogen bonded complexes formed between the square pyramidal Fe(CO)(5) with HX (X = F, Cl, Br), showing X-H center dot center dot center dot Fe interactions, have been investigated theoretically using density functional theory (DFT) including dispersion correction. Geometry, interaction energy, and large red shift of about 400 cm(-1) in the FIX stretching frequency confirm X-H center dot center dot center dot Fe hydrogen bond formation. In the (CO)(5)Fe center dot center dot center dot HBr complex, following the significant red shift, the HBr stretching mode is coupled with the carbonyl stretching modes. This clearly affects the correlation between frequency shift and binding energy, which is a hallmark of hydrogen bonds. Atoms in Molecule (AIM) theoretical analyses show the presence of a bond critical point between the iron and the hydrogen of FIX and significant mutual penetration. These X-H center dot center dot center dot Fe hydrogen bonds follow most but not all of the eight criteria proposed by Koch and Popelier (J. Phys. Chem. 1995, 99, 9747) based on their investigations on C-H center dot center dot center dot O hydrogen bonds. Natural bond orbital (NBO) analysis indicates charge transfer from the organometallic system to the hydrogen bond donor. However, there is no correlation between the extent of charge transfer and interaction,energy, contrary to what is proposed in the recent IUPAC recommendation (Pure Appl.. Chem. 2011, 83, 1637). The ``hydrogen bond radius'' for iron has been determined to be 1.60 +/- 0.02 angstrom, and not surprisingly it is between the covalent (127 angstrom) and van der Waals (2.0) radii of Fe. DFT and AIM theoretical studies reveal that Fe in square pyramidal Fe(CO)(5) can also form halogen bond with CIF and ClH as ``halogen bond donor''. Both these complexes show mutual penetration as well, though the Fe center dot center dot center dot Cl distance is closer to the sum of van der Waals radii of Fe and Cl in (CO)5Fe center dot center dot center dot ClH, and it is about 1 angstrom less in (CO)(5)Fe center dot center dot center dot ClF.

Dynamics of the chemical bond: inter- and intra-molecular hydrogen bond

In this discussion, we show that a static definition of a `bond' is not viable by looking at a few examples for both inter-and intra-molecular hydrogen bonding. This follows from our earlier work (Goswami and Arunan, Phys. Chem. Chem. Phys. 2009, 11, 8974) which showed a practical way to differentiate `hydrogen bonding' from `van der Waals interaction'. We report results from ab initio and atoms in molecules theoretical calculations for a series of Rg center dot center dot center dot HX complexes (Rg = He/Ne/Ar and X = F/Cl/Br) and ethane-1,2-diol. Results for the Rg center dot center dot center dot HX/DX complexes show that Rg center dot center dot center dot DX could have a `deuterium bond' even when Rg center dot center dot center dot HX is not `hydrogen bonded', according to the practical criterion given by Goswami and Arunan. Results for ethane-1,2-diol show that an `intra-molecular hydrogen bond' can appear during a normal mode vibration which is dominated by the O center dot center dot center dot O stretching, though a `bond' is not found in the equilibrium structure. This dynamical `bond' formation may nevertheless be important in ensuring the continuity of electron density across a molecule. In the former case, a vibration `breaks' an existing bond and in the later case, a vibration leads to `bond' formation. In both cases, the molecule/complex stays bound irrespective of what happens to this `hydrogen bond'. Both these cases push the borders on the recent IUPAC recommendation on hydrogen bonding (Arunan et al. Pure. Appl. Chem. 2011, 83 1637) and justify the inclusive nature of the definition.

Query Click and Text Similarity Graph for Query Suggestions

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.