IKDD

This study present SocialStories - a system based on incremental clustering for streaming tweets, for identifying fine-grained stories within a broader trending topic on Twitter. The contributions include a novel tf-metric, called the inverse cluster ...

Recently Kulkarni et al. [20] proposed an approach for collective disambiguation of entity mentions occurring in natural language text. Their model achieves disambiguation by efficiently computing exact MAP inference in a binary labeled Markov Random ...

Shapelets are discriminative patterns in time series, that best predict the target variable when their distances to the respective time series are used as features for a classifier. Since the shapelet is simply any time series of some length less than ...

Detection and assessment of spatio-temporal change pattern is a challenging task, and may provide insights into various spatio-temporal changes, like urban sprawl monitoring, surveillance of epidemics due to infectious diseases etc. The existing spatio-...

Community structures are inherent in social networks and finding them is an interesting and well-studied problem. Finding community structures in social networks is similar to locating densely connected clusters of nodes in a graph. One of the popular ...

People extensively use username to lookup users, their profiles and tweets that mention them via Twitter search engine. Often, the searched username is outdated due to a recent username change and no longer refers to the user of interest. Search by the ...

The largest Media and Entertainment (M&E) web portals today cater to more than 100 Million unique visitors every month. In Customer Relationship Management, customer segmentation plays an important role, with the goal of targeting different products for ...

Online Micro-blogging Social Media websites like Twitter are being used as a real-time platform for information sharing and communication during planning and mobilization of civil unrest events. We conduct a study of more than 1.5 million English Tweets ...

In this paper, we present an extended 2-step probabilistic LGTS (PLGTS) transition system which aims to identify the network structure and stochastic nature of biological processes using time series data. This work is a step towards system ...

We first propose an online learning model wherein rewards for different actions/arms used by the user can be correlated and the reward stream can be non-stationary. Thus, this extends the standard multi-armed bandit learning model. We propose two ...

Location based services and Geospatial web applications have become popular in recent years due to wide adoption of mobile devices. Search and recommendation of places or Points of Interests (PoIs) are prominent services available on them. The ...

Social media platform are increasingly becoming a rich source of information for capturing the views and opinions of online customers. Major brands listen to the social streams to understand the general pulse of their online community. The foremost task ...

Community-driven Question Answering (Q&A) platforms are gaining popularity now-a-days and the number of posts on such platforms are increasing tremendously. Thus, the challenge to keep these platforms noise-free is attracting the interest of research ...

Protein-protein interaction (PPI) networks are valuable biological data source which contain rich information useful for protein function prediction. The PPI network data obtained from high-throughput experiments is known to be noisy and incomplete. In ...

In the digital era vast amount of data are collected and shared for purpose of research and analysis. These data contain sensitive information about the people and organizations which needs to be protected during the process of data mining. This work ...

Indian Citizens are beginning to express themselves via social media on a regular basis on various issues. Government of India have started an initiated called as Mygov.in as a collaborative portal where citizens can voice their opinions via free form ...

A well known technique for embedding high dimensional objects in two or three dimensional space is the t-distributed stochastic neighbour embedding (t-SNE). The t-SNE minimizes the Kullback-Liebler (KL) divergence between two probability distributions, ...

Traditional point based clustering methods such as k-means [1], k-median [2], etc. work by partitioning the data into clusters based on the cluster prototype points. These methods perform poorly in case when data is not distributed around several ...

Sentiment drifts due to people changing their opinions instantly on microblogs e.g. Twitter, are a major challenge in sentiment analysis. In this paper, we have developed a method that selects most frequent messages from a relevant message set ...

Examining work activity patterns is a problem of enduring research in organizations. The fortuitous availability of a whole new set of data collection mechanisms such as mobiles, activity loggers, GPS based location detectors, provide us new ways of ...

Community discovery is an important problem that has been addressed in social networks through multiple perspectives. Most of these algorithms discover disjoint communities and yield widely varying results with regard to number of communities as well as ...

In the banner advertising scenario, an advertiser aims to reach the maximum number of potential visitors and a publisher tries to meet the requests of increased number of advertisers to maximize the revenue. In the literature, a model was introduced to ...

We propose an unsupervised approach to extract all competing algorithms present in a given scholarly article. The algorithm names are treated as named entities and natural language processing techniques are used to extract them. All extracted entity ...

Users often seek for information by submitting query consisting of keywords may belong to multiple topics, representing overlapping concepts. Objective of the work is to classify the query into a topic class label by considering the query keywords ...

Feature selection by reduct computation is the key technique for knowledge acquistion using rough set theory. Existing MapReduce based reduct algorithms use Hadoop Map Reduce framework, which is not suitable for iterative algorithms. Paper aims to ...

Citizens tend to discuss issues in public forums, social media, and web blogs. Given that issues related to public transportation are most actively reported across web-based sources, we present a holistic framework for collection, categorization, ...

More than a million engineers enter the global workforce every year. A relevant question is what determines the jobs and salaries these engineers are offered right after graduation. Previous studies have shown the influence of various factors such as ...