Manish Gupta

Manish Gupta
International Institute of Information Technology, Hyderabad | IIIT · Language Technology Research Center (LTRC)

About

45
Publications
12,368
Reads
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928
Citations
Citations since 2016
42 Research Items
890 Citations
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2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250
2016201720182019202020212022050100150200250

Publications

Publications (45)
Chapter
Query-document topic match is one of the central signals for ranked information retrieval. Returning documents which are too broad or insufficient or off-topic compared to the query leads to a poor user experience. Thus, given a query and a document, it is critical to estimate degree of topical mismatch between the two. Previous work has either foc...
Chapter
Social media platforms have democratized the publication process resulting into easy and viral propagation of information. However, spread of rumors via such media often results into undesired and extremely impactful political, economic, social, psychological and criminal consequences. Several manual as well as automated efforts have been undertake...
Preprint
Full-text available
The exponential rise of online social media has enabled the creation, distribution, and consumption of information at an unprecedented rate. However, it has also led to the burgeoning of various forms of online abuse. Increasing cases of online antisemitism have become one of the major concerns because of its socio-political consequences. Unlike ot...
Chapter
Although several automatic itinerary generation services have made travel planning easy, often times travellers find themselves in unique situations where they cannot make the best out of their trip. Visitors differ in terms of many factors such as suffering from a disability, being of a particular dietary preference, travelling with a toddler, etc...
Preprint
Full-text available
Automatic text summarization has been widely studied as an important task in natural language processing. Traditionally, various feature engineering and machine learning based systems have been proposed for extractive as well as abstractive text summarization. Recently, deep learning based, specifically Transformer-based systems have been immensely...
Preprint
Although several automatic itinerary generation services have made travel planning easy, often times travellers find themselves in unique situations where they cannot make the best out of their trip. Visitors differ in terms of many factors such as suffering from a disability, being of a particular dietary preference, travelling with a toddler, etc...
Preprint
Full-text available
While extensive popularity of online social media platforms has made information dissemination faster, it has also resulted in widespread online abuse of different types like hate speech, offensive language, sexist and racist opinions, etc. Detection and curtailment of such abusive content is critical for avoiding its psychological impact on victim...
Preprint
Full-text available
In recent years, the fields of natural language processing (NLP) and information retrieval (IR) have made tremendous progress thanks to deep learning models like Recurrent Neural Networks (RNNs), Gated Recurrent Units (GRUs) and Long Short-Term Memory (LSTMs) networks, and Transformer based models like Bidirectional Encoder Representations from Tra...
Chapter
Informational chatbots provide a highly effective medium for improving operational efficiency in answering customer queries for any enterprise. Chatbots are also preferred by users/customers since unlike other alternatives like calling customer care or browsing over FAQ pages, chatbots provide instant responses, are easy to use, are less invasive a...
Conference Paper
Every two minutes one woman dies of cervical cancer globally, due to lack of sufficient screening. Given a whole slide image (WSI) obtained by scanning a microscope glass slide for a Liquid Based Cytology (LBC) based Pap test, our goal is to assist the pathologist to determine the presence of pre-cancerous or cancerous cervical anomalies. Inter-ann...
Chapter
Recently, deep learning techniques have been widely used for medical image analysis. While there exists some work on deep learning for ophthalmology, there is little work on multi-disease predictions from retinal fundus images. Also, most of the work is based on small datasets. In this work, given a fundus image, we focus on three tasks related to...
Conference Paper
Full-text available
Automatic text summarization has been widely studied as an important task in natural language processing. Traditionally, various feature engineering and machine learning based systems have been proposed for extractive as well as abstractive text summarization. Recently, deep learning based, specifically Transformer-based systems have been immensely...
Conference Paper
Social network and publishing platforms, such as Twitter, support the concept of a secret proprietary verification process, for handles they deem worthy of platform-wide public interest. In line with significant prior work which suggests that possessing such a status symbolizes enhanced credibility in the eyes of the platform audience, a verified b...
Chapter
Full-text available
Users have been trained to type keyword queries on search engines. However, recently there has been a significant rise in the number of verbose queries. Often times such queries are not well-formed. The lack of well-formedness in the query might adversely impact the downstream pipeline which processes these queries. A well-formed natural language q...
Preprint
Full-text available
Social network and publishing platforms, such as Twitter, support the concept of a secret proprietary verification process, for handles they deem worthy of platform-wide public interest. In line with significant prior work which suggests that possessing such a status symbolizes enhanced credibility in the eyes of the platform audience, a verified b...
Preprint
Full-text available
Social network and publishing platforms, such as Twitter, support the concept of verification. Verified accounts are deemed worthy of platform-wide public interest and are separately authenticated by the platform itself. There have been repeated assertions by these platforms about verification not being tantamount to endorsement. However, a signifi...
Article
Opinion list (OL) queries like “valentines day gift ideas” and “best anniversary messages for your parents” are quite popular on web search engines. Users expect instant answers comprising of a list of relevant items (OL) for such a query. Surprisingly, current search engines do not provide any crisp instant answers for queries in this critical que...
Conference Paper
Full-text available
Cybercriminals abuse Online Social Networks (OSNs) to lure victims into a variety of spam. Among different spam types, a less explored area is OSN abuse that leverages the telephony channel to defraud users. Phone numbers are advertized via OSNs, and users are tricked into calling these numbers. To expand the reach of such scam / spam campaigns, ph...
Conference Paper
Full-text available
Automated multi-document extractive text summarization is a widely studied research problem in the field of natural language understanding. Such extractive mechanisms compute in some form the worthiness of a sentence to be included into the summary. While the conventional approaches rely on human crafted document-independent features to generate a...
Article
Full-text available
Analyzing the temporal behavior of nodes in time-varying graphs is useful for many applications such as targeted advertising, community evolution and outlier detection. In this paper, we present a novel approach, STWalk, for learning trajectory representations of nodes in temporal graphs. The proposed framework makes use of structural properties of...
Conference Paper
Full-text available
Social list queries like 'valentines day gift ideas', 'best anniversary messages for your parents', etc. are quite popular on web search engines. Users expect instant answers comprising of a list of relevant items (social list) for such a query. Surprisingly, current search engines do not provide any crisp instant answers for queries in this critic...
Article
Full-text available
Inferring trust relations between social media users is critical for a number of applications wherein users seek credible information. The fact that available trust relations are scarce and skewed makes trust prediction a challenging task. To the best of our knowledge, this is the first work on exploring representation learning for trust prediction...
Article
Full-text available
Hate speech detection on Twitter is critical for applications like controversial event extraction, building AI chatterbots, content recommendation, and sentiment analysis. We define this task as being able to classify a tweet as racist, sexist or neither. The complexity of the natural language constructs makes this task very challenging. We perform...
Article
Research in analysis of microblogging platforms is experiencing a renewed surge with a large number of works applying representation learning models for applications like sentiment analysis, semantic textual similarity computation, hashtag prediction, etc. Although the performance of the representation learning models has been better than the tradi...
Conference Paper
In this work we propose a novel representation learning model which computes semantic representations for tweets accurately. Our model systematically exploits the chronologically adjacent tweets (‘context’) from users’ Twitter timelines for this task. Further, we make our model user-aware so that it can do well in modeling the target tweet by explo...
Article
Full-text available
The study of networks has emerged in diverse disciplines as a means of analyzing complex relationship data. Beyond graph analysis tasks like graph query processing, link analysis, influence propagation, there has recently been some work in the area of outlier detection for information network data. Although various kinds of outliers have been studi...
Article
In this work we propose a novel representation learning model which computes semantic representations for tweets accurately. Our model systematically exploits the chronologically adjacent tweets ('context') from users' Twitter timelines for this task. Further, we make our model user-aware so that it can do well in modeling the target tweet by explo...
Article
Research in social media analysis is experiencing a recent surge with a large number of works applying representation learning models to solve high-level syntactico-semantic tasks such as sentiment analysis, semantic textual similarity computation, hashtag prediction and so on. Although the performance of the representation learning models are bett...
Conference Paper
Doc2Sent2Vec is an unsupervised approach to learn low-dimensional feature vector (or embedding) for a document. This embedding captures the semantics of the document and can be fed as input to machine learning algorithms to solve a myriad number of applications in the field of data mining and information retrieval. Some of these applications includ...
Conference Paper
LASIK (Laser-Assisted in SItu Keratomileusis) surgeries have been quite popular for treatment of myopia (nearsightedness), hyperopia (farsightedness) and astigmatism over the past two decades. In the past decade, over 10 million LASIK procedures had been performed in the United States alone with an average cost of approximately $2000 USD per surger...
Conference Paper
In this paper, we consider the problem of learning representations for authors from bibliographic co-authorship networks. Existing methods for deep learning on graphs, such as DeepWalk, suffer from link sparsity problem as they focus on modeling the link information only. We hypothesize that capturing both the content and link information in a unif...
Patent
Full-text available
Methods, systems and computer program products are provided for social networking. In one method, a network builder receives a digital object from the user. The digital object contains information associated with the user. The network builder extracts the information associated with the user from the digital object. The network builder further acce...
Article
Though Twitter acts as a realtime news source with people acting as sensors and sending event updates from all over the world, rumors spread via Twitter have been noted to cause considerable damage. Given a set of popular Twitter events along with related users and tweets, we study the problem of automatically assessing the credibility of such even...
Article
Protein sequences vary in their length and are not readily amenable to conventional data mining techniques that need mapping in a fixed dimensional space. Thus, majority of the current methods for protein sequence classification are based on alignment of the query sequence either with a sequence or a profile of the sequence family. We present a met...

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