Palakorn Achananuparp

Singapore Management University | smu · Living Analytics Research Centre

The ability to accurately judge the similarity between natural language sentences is critical to the performance of several applications such as text mining, question answering, and text summarization. Given two sentences, an effective similarity measure should be able to determine whether the sentences are semantically equivalent or not, taking in...

Summarizing and analyzing Twitter content is an important and challenging task. In this paper, we propose to extract topical keyphrases as one way to summarize Twitter. We propose a context-sensitive topical PageRank method for keyword ranking and a probabilistic scoring function that considers both relevance and interestingness of keyphrases for k...

Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to...

What is the effect of (1) popular individuals, and (2) community structures on the retransmission of socially contagious behavior? We examine a community of Twitter users over a five month period, operationalizing social contagion as ‘retweeting’, and social structure as the count of subgraphs (small patterns of ties and nodes) between users in the...

The recent success of large language models (LLMs) has attracted widespread interest to develop role-playing conversational agents personalized to the characteristics and styles of different speakers to enhance their abilities to perform both general and special purpose dialogue tasks. However, the ability to personalize the generated utterances to...

Introduction With in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity. Methods 280 participants were recruited between May and November 2022. Participants completed a questionnair...

Next-basket recommendation (NBR) is a recommendation task that predicts a basket or a set of items a user is likely to adopt next based on his/her history of basket adoption sequences. It enables a wide range of novel applications and services from predicting next basket of items for grocery shopping to recommending food items a user is likely to c...

Next-basket recommendation (NBR) is a recommendation task that predicts a basket or a set of items a user is likely to adopt next based on his/her history of basket adoption sequences. It enables a wide range of novel applications and services from predicting next basket of items for grocery shopping to recommending food items a user is likely to c...

Background Artificial intelligence (AI) has the potential to improve the efficiency and effectiveness of health care service delivery. However, the perceptions and needs of such systems remain elusive, hindering efforts to promote AI adoption in health care. Objective This study aims to provide an overview of the perceptions and needs of AI to inc...

BACKGROUND Artificial intelligence (AI) has the potential to improve the efficiency and effectiveness of health care service delivery. However, the perceptions and needs of such systems remain elusive, hindering efforts to promote AI adoption in health care. OBJECTIVE This study aims to provide an overview of the perceptions and needs of AI to inc...

Food retrieval is an important task to perform analysis of food related information, where we are interested in retrieving relevant information about the queried food item such as ingredients, cooking instructions, etc. In this paper, we investigate cross-modal retrieval between food images and cooking recipes. The goal is to learn an embedding of...

We present an invert-and-edit framework to automatically transform facial weight of an input face image to look thinner or heavier by leveraging semantic facial attributes encoded in the latent space of Generative Adversarial Networks (GANs). Using a pre-trained StyleGAN as the underlying generator, we first employ an optimization-based embedding m...

Recent research has identified a few design flaws in popular mobile health (mHealth) applications for promoting healthy eating lifestyle, such as mobile food journals. These include tediousness of manual food logging, inadequate food database coverage, and a lack of healthy dietary goal setting. To address these issues, we present Foodbot, a chatbo...

Cross-modal food retrieval is an important task to perform analysis of food-related information, such as food images and cooking recipes. The goal is to learn an embedding of images and recipes in a common feature space, so that precise matching can be realized. Compared with existing cross-modal retrieval approaches, two major challenges in this s...

Interests in the automatic generation of cooking recipes have been growing steadily over the past few years thanks to a large amount of online cooking recipes. We present RecipeGPT, a novel online recipe generation and evaluation system. The system provides two modes of text generations: (1) instruction generation from given recipe title and ingred...

Human beings are creatures of habit. In their daily life, people tend to repeatedly consume similar types of food items over several days and occasionally switch to consuming different types of items when the consumptions become overly monotonous. However, the novel and repeat consumption behaviors have not been studied in food recommendation resea...

Consumption of diets with low glycemic impact is highly recommended for diabetics and pre-diabetics as it helps maintain their blood glucose levels. However, laboratory analysis of dietary glycemic potency is time-consuming and expensive. In this paper, we explore a data-driven approach utilizing online crowdsourcing and machine learning to estimat...

Human beings are creatures of habit. In their daily life, people tend to repeatedly consume similar types of food items over several days and occasionally switch to consuming different types of items when the consumptions become overly monotonous. However, the novel and repeat consumption behaviors have not been studied in food recommendation resea...

Consumption of diets with low glycemic impact is highly recommended for diabetics and pre-diabetics as it helps maintain their blood glucose levels. However, laboratory analysis of dietary glycemic potency is time-consuming and expensive. In this paper, we explore a data-driven approach utilizing online crowdsourcing and machine learning to estimat...

An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular diseases. Moreover, food logging can help fitness enthusiasts, and people who wanting to achieve a target weight. However, food-logging is cumbersome, and requires not o...

This dataset contains a rich set of data consisting of daily food logging, self-report subjective well-being evaluation, and demographic information of 245 Healthy365, MyFitnessPal, and Fitbit users over 30-day period. The data were collected during the randomized controlled trial called Eat & Tell conducted in 2017. If you use this dataset in a sc...

An important aspect of health monitoring is effective logging of food consumption. This can help management of diet-related diseases like obesity, diabetes, and even cardiovascular diseases. Moreover, food logging can help fitness enthusiasts, and people who wanting to achieve a target weight. However, food-logging is cumbersome, and requires not o...

A growing body of evidence has shown that incorporating behavioral economics principles into the design of financial incentive programs helps improve their cost-effectiveness, promote individuals' short-term engagement, and increase compliance in health behavior interventions. Yet, their effects on long-term engagement have not been fully examined....

Past research has shown the benefits of food journaling in promoting mindful eating and healthier food choices. However, the links between journaling and healthy eating have not been thoroughly examined. Beyond caloric restriction, do journalers consistently and sufficiently consume healthful diets? How different are their eating habits compared to...

A growing body of evidence has shown that incorporating behavioral economics principles into the design of financial incentive programs helps improve their cost-effectiveness, promote individuals' short-term engagement, and increase compliance in health behavior interventions. Yet, their effects on long-term engagement have not been fully examined....

This dataset contains 1.9 million meals logged by 9.8K MyFitnessPal users on 71K food items from September 2014 through April 2015. Food items with similar textual description have been grouped together. The dataset consists of data and item files. Their formats are described below. data.tsv: Each line is a tab separated list of meal_id, user_id...

In this paper, we explore the problem of identifying substitute relationship between food pairs from real-world food consumption data as the first step towards the healthier food recommendation. Our method is inspired by the distributional hypothesis in linguistics. Specifically, we assume that foods that are consumed in similar contexts are more l...

Authority users often play important roles in a social system. They are expected to write good reviews at product review sites; provide high quality answers in question answering systems; and share interesting content in social networks. In the context of marketing and advertising, knowing how users react to emails and messages from authority sende...

To support people trying to lose weight and stay healthy, more and more fitness apps have sprung up including the ability to track both calories intake and expenditure. Users of such apps are part of a wider " quantified self " movement and many opt-in to publicly share their logged data. In this paper, we use public food diaries of more than 4,000...

Geotagged social media is becoming highly popular as social media access is now made very easy through a wide range of mobile apps which automatically detect and augment social media posts with geo-locations. In this paper, we analyze two kinds of location-based patterns. The first is the association between location attributes and the locations of...

Each entry contains 3 values separated by tab: Main category, subcategory, and food entity name

This dataset contains 587,187 days of food diary records logged by 9.9K MyFitnessPal users from September 2014 through April 2015. Each line is a tab-separated list of: - Anonymized user ID - Diary date - List of food entries and nutrients (as JSON objects) - Daily aggregate of nutrient intake and goal (as JSON objects). If you use the dataset...

Tracking user browsing data and measuring the effectiveness of website design and web services are important to businesses that want to attract the consumers today who spend much more time online than before. Instead of using randomized controlled experiments, the existing approach simply tracks user browsing behaviors before and after a change is...

With the widespread adoption of the Web, many companies and organizations have established websites that provide information and support online transactions (e.g., buying products or viewing content). Unfortunately, users have limited attention to spare for interacting with online sites. Hence, it is of utmost importance to design sites that attrac...

Gaming expertise is usually accumulated through playing or watching many game instances, and identifying critical moments in these game instances called turning points. Turning point rules (shorten as TPRs) are game patterns that almost always lead to some irreversible outcomes. In this paper, we formulate the notion of irreversible outcome propert...

Unlike standard web search, people search microblog mes-sages to look for temporally relevant information. Due to the recency nature of microblogs and a massive amount of data generated by users of popular services such as Twitter, it is challenging to design and imple-ment a microblog retrieval system that satisfies the searcher and tech-nical req...

Real-time microblogging systems such as Twitter offer users an easy and lightweight means to exchange information. Instead of writing formal and lengthy messages, microbloggers prefer to frequently broadcast several short messages to be read by other users. Only when messages are interesting, are they propagated further by the readers. In this arti...

In-game actions of real-time strategy (RTS) games are extremely useful in determining the players' strategies, ana-lyzing their behaviors and recommending ways to improve their play skills. Unfortunately, unstructured sequences of in-game actions are hardly informative enough for these analyses. The inconsistency we observed in human annotation of...

Millions of people, including those in the soft-ware engineering communities have turned to microblogging services, such as Twitter, as a means to quickly disseminate information. A number of past studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting information is stored in these microblogs. However, microblogs...

Microblogging has recently become a popular means to disseminate information among millions of people. Interest-ingly, software developers also use microblog to communicate with one another. In Twitter, many developers microblog or tweet about bugs, new IDEs, new programming languages, etc. Different from traditional media, microblog users tend to...

The way Twitter and other microblogging networks work is to have users create follow links among one another, and create short messages to their followers. Most of the time, the creation of follow links to other users does not require approval from the latter. Therefore, it is very easy for a user to create such links. On the other hand, the same c...

1732 event logs of actions performed by players in Starcraft II public replays downloaded from GameReplays.org. The Data Set consists of 1732 log files (Size: 55 MB) compressed into a Zip archive (Size: 9.3 MB).

Microblogging is a new trend to communicate and to disseminate information. One microblog post could potentially reach millions of users. Millions of microblogs are generated on a daily basis on popular sites such as Twitter. The popularity of microblogging among programmers, software engineers, and software users has also led to their use of micro...

Twitter is a popular microblogging site where users can easily use mobile phones or desktop machines to generate short messages to be shared with others in realtime. Twitter has seen heavy usage in many recent international events including Japan earthquake, Iran election, etc. In such events, many tweets may become viral for different reasons. In...

Socialness refers to the ability to elicit social in- teraction and social links among people. It is a concept often associated with individuals. Although there are tangible benefits in socialness, there is little research in its modeling. In this paper, we study socialness as a property that can be associated with items, beyond its traditional ass...

We present NegativeRank, a novel graph-based sentence ranking model to improve the diversity of focused summary by performing random walks over sentence graph with negative edge weights. Unlike the typical eigenvector centrality ranking, our method models the redundancy among sentence nodes as the negative edges. The negative edges can be thought o...

We present a novel graph ranking model to extract a diverse set of answers for complex questions via random walks over a negative-edge graph. We assign a negative sign to edge weights in an answer graph to model the redundancy relation among the answer nodes. Negative edges can be thought of as the propagation of negative endorsements or disapprova...

In this article, we present a graph-based knowledge representation for biomedical digital library literature clustering. An efficient clustering method is developed to identify the ontology-enriched k-highest density term subgraphs that capture the core semantic relationship information about each document cluster. The distance between each documen...

The World Cancer Report urges nations to act to address the alarming increase in global cancer rates. It is estimated that risk factor reduction and appropriate screening could prevent as many as one third of cancers worldwide. However, while effective education to reduce risk factors and increase screening depends on the management and analysis of...

We propose a ranking model to diversify answers of non-factoid questions based on an inverse notion of graph connectivity. By representing a collection of candidate answers as a graph, we posit that novelty, a measure of diversity, is inversely proportional to answer vertices' connectivity. Hence, unlike the typical graph ranking models, which scor...

Biomedical images and captions are one of the major sources of information in online biomedical publications. They often contain the most important results to be reported, and provide rich information about the main themes in published papers. In the data mining and information retrieval community, there are a lot of research works on using text mi...

We introduce our QA system AskDragon which employs a novel lightweight local context analysis technique to handling two broad classes of factoid questions, entity and numeric questions. The local context analysis module dramatically improves the efficiency of QA systems without sacrificing high accuracy performance.

In this paper, we present a new approach that incorporates semantic structure of sentences, in a form of verb-argument structure, to measure semantic similarity between sentences. The variability of natural language expression makes it difficult for existing text similarity measures to accurately identify semantically similar sentences since senten...

Digital reference services normally rely on human experts to provide quality answers to the user requests via online communication tools. As the services gain more popularity, more experts are needed to keep up with a growing demand. Alternatively, automated question answering module can help shorten the question-answering cycle. When the system re...

In this article, we present a graph-based knowledge representation for biomedical digital library literature clustering An efficient clustering method is developed to identify the ontology-enriched k-highest density term subgraphs that capture the core semantic relationship information about each document cluster The distance between each document...

Document representation is one of the crucial components that determine the effectiveness of text classification tasks. Traditional document representation approaches typically adopt a popular bag-of-word method as the underlying document representation. Although itpsilas a simple and efficient method, the major shortcoming of bag-of-word represent...

This paper proposes some expanded rough set models with maximal compatible classes as primitive granules, introduces two new granules for extending rough set model, and designs algorithms to solve maximal compatible classes, to find the lower and upper approximations according to the newly granules, to compute reducts and minimal reducts with attri...

We describe the Image Tagger system - a web-based tool for supporting collaborative image indexing by students. The tool has been used in three successive graduate-level classes on content representation. To fully satisfy the class' requirements and provide support for student indexing activities, it was designed and developed iteratively in accord...

In this paper, we explore how global ranking method in conjunction with local density method help identify meaningful term clusters from ontology enriched graph representation of biomedical literature corpus. One big problem with document clustering is how to discount the effects of class-unspecific general terms and strengthen the effects of class...

Large quantities of historical newspapers are being digitized and OCRd. We describe a framework for processing the OCRd text to identify articles and extract metadata for them. We describe the article schema and provide examples of features that facilitate automatic indexing of them. For this processing, we employ lexical semantics, structural mode...

While several digital repository systems are widely adopted as tools for building digital libraries, they are rather complex or required major customization to be used as tools for teaching principles of repository management. As these tools offer a wide range of functionalities to support all kinds of applications, they are too complex to be used...

Content-based implicit user modeling techniques usually employ traditional term vector as a representation of the user's interest. However, due to the problem of dimensionality in vector space model, a simple term vector is not a sufficient representation of the user model as it ignores the semantic relations between terms. In this paper, we presen...

We developed a simple Web-based prototype to familiarize students with digital library tools. To assist the students with the indexing task, the prototype provided basic functionalities, including metadata input form, photo search interface. The students generally expressed a positive feedback toward the use of digital library tools in their image...

Electronic voting is slowly making its way into American politics. At the same time, more voters and potential voters are using online news and political information sources to help them make voting choices. We conducted a mock-voting study, using real candidates, issues, and campaign materials. Political information was browsed either online or on...