著者

市川 淳 三輪 和久 寺井 仁

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.30, no.3, pp.585-594, 2015-05-01 (Released:2015-05-01)

参考文献数

25

被引用文献数

3 1

---

For skill acquisition that needs periodic body movements as cascade juggling, the establishment of stable body movements seems crucial. We investigated them in each of the learning stages defined by the Beek and van Santvoord (1992) framework. In addition, we investigated participants' verbal reports about what was intentionally concerned for achieving optimum learning in practice. In the experiment, novices practiced three-ball cascade juggling over a period of one week. We focused on two types of stabilities: the stability of chest movement representing torso movement, and another stability of wrist movement representing arm swing. The result revealed that the skills for establishing stabilities of torso movement and arm swing were acquired sequentially. In this case, the stability of arm swing emerged between Stage 2 (by 50 successive catches) and Stage 3 (by over 100 successive catches), and another stability of torso movement emerged between Stage 3 and the expert stage in which jugglers had acquired complete skills for performing five-ball cascade juggling. The result also showed that in the establishment of stable arm swing, the development of the stability occurred only in passive catching behavior, but did not in active tossing behavior. Additionally, we found that the participants who did not develop beyond Stage 1 (by 10 successive catches) trained themselves while focusing on their specific physical movements.

著者

水門 善之 田邊 洋人

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.37, no.2, pp.37-2_D-LB2, 2022-03-01 (Released:2022-03-01)

参考文献数

12

---

In recent years, the importance of responding to climate change has increased, and various countries have set greenhouse gas emission reduction targets centered on CO₂ (Carbon Dioxide). In this study, we analyzed the relationship between macroeconomic activity and CO₂ emissions amid growing discussions on CO₂ emissions. Recently, while the positive correlation between GDP and CO₂ emissions on a level basis, which had been confirmed in the past, is collapsing mainly in Europe and the United States. However, it this research, we converted the GDP and CO₂ emissions data to a yearly change rate in order to mitigate the effects of structural environmental changes and we confirmed that a positive correlation was maintained between emissions and economic growth rate. Then, in this research, in order to immediately grasp the CO₂ emission status, we used the CO₂ concentration data which was measured using the observation information from artificial satellites (GOSAT, Greenhouse gases Observing SATellite). We proposed an effective method for grasping the macroeconomic situation in real time. In addition, in the proposed method, the estimation accuracy of the economic model was improved by using fine-grained satellite information as a feature quantity.

著者

松波 夏樹 唐鎌 聡太郎

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.5, pp.G-L45_1-6, 2021-09-01 (Released:2021-09-01)

参考文献数

14

---

Towards close collaboration between a human and a large number of AI systems, we propose to design an AI agent with two technical elements. The first is the use of a modeling approach that enables us to know what AI agents are trying to do. The second is the use of a multi-agent consensus building algorithm. A good combination of these two, a human and a group of AI agents were put together as one team. In this paper, we explain a configuration using a Behavior Tree and a Contract Net Protocol as a concrete example. In addition, we propose a method of applying reinforcement learning in which the intentions of the AI agents can be easily grasped by a human. The effectiveness and feasibility of this approach were evaluated with teams in a simulated Tail Tag game. Matches were held with up to 29 AI agents and 1 person on one team and 30 people on the other team. The results indicate that our approach works almost evenly with human-human collaboration by sharing roles between a human and AI swarm.

著者

髙嶺 潮 遠藤 聡志

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.5, pp.B-KC6_1-9, 2021-09-01 (Released:2021-09-01)

参考文献数

11

---

Scene understanding is a central problem in a field of computer vision. Depth estimation, in particular, is one of the important applications in scene understanding, robotics, and 3-D reconstruction. Estimating a dense depth map from a single image is receiving increased attention because a monocular camera is popular, small and suitable for a wide range of environments. In addition, both multi-task learning and multi-stream, which use unlabeled information, improve the monocular depth estimation efficiently. However, there are only a few networks optimized for both of them. Therefore, in this paper, we propose a monocular depth estimation task with a multi-task and multistream network architecture. Furthermore, the integrated network which we develop makes use of depth gradient information and can be applied to both supervised and unsupervised learning. In our experiments, we confirmed that our supervised learning architecture improves the accuracy of depth estimation by 0.13 m on average. Additionally, the experimental result on unsupervised learning found that it improved structure-from-motion performance.

著者

本間 広樹 小町 守

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.37, no.1, pp.B-L22_1-14, 2022-01-01 (Released:2022-01-01)

参考文献数

33

---

There are several problems in applying grammatical error correction (GEC) to a writing support system. One of them is the handling of sentences in the middle of the input. Till date, the performance of GEC for incomplete sentences is not well-known. Hence, we analyze the performance of GEC model for incomplete sentences. Another problem is the correction speed. When the speed is slow, the usability of the system is limited, and the user experience is degraded. Therefore, in this study, we also focus on the non-autoregressive (NAR) model, which is a widely studied fast decoding method. We perform GEC in Japanese with traditional autoregressive and recent NAR models and analyze their accuracy and speed. Furthermore, in this study, we construct a writing support system with a grammatical error correction function. Specifically, the trained NAR model is embedded in the back-end system. We confirm the system’s effectiveness by both objective and subjective evaluations.

著者

福馬 智生 鳥海 不二夫

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.5, pp.F-JC3_1-9, 2020-09-01 (Released:2020-09-01)

参考文献数

27

---

Latent factor models such as Matrix Factorization have become the default choice for recommender systems due to their performance and scalability. However, such algorithms have two disadvantages. First, these models suffer from data sparsity. Second, they fail to account for model uncertainty. In this paper, we exploit a meta learning strategy to address these problems. The key idea behind our method is to learn predictive distributions conditioned on context sets of arbitrary size of user/item interaction information. Our proposed framework has the advantages of being easy to implement and applicable to any existing latent factor models, providing uncertainty capabilities. We demonstrate the significant superior performance of our model over previous state-of-the-art methods, especially for sparse data in the top-N recommendation task.

著者

武田 惇史 鳥海 不二夫

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.6, pp.D-L36_1-12, 2021-11-01 (Released:2021-11-01)

参考文献数

21

---

One of the AI systems introduced into our society in recent years is a system that negotiates and collaborates with users by presenting and recommending information through dialogues with multiple users. In general, users have different cultures and values. Therefore, the system must be able to estimate those values and then adapt its behavior to the user. In this study, we focus on the "werewolf game" as a benchmark for this type of technology. The werewolf game is an imperfect information game in which the game proceeds through communication. A werewolf game is a team game and has both cooperative and adversarial characteristics. In werewolf games, it is important not to cause conflicts among allies due to differences in culture and way of thinking. In this study, we first create multiple agent groups with different cultures. Then, we show that there is no specific strong strategy, and that the optimal strategy is different for each group. Then, we build an agent that can estimate the culture of the strategy that players other than itself are following, and can act in such a way that it adapts itself to that culture, and conduct an evaluation based on the winning rate. The results show that the proposed agent is able to adapt to the group and increase its winning rate under certain limitations.

著者

後藤 匡史 長木 悠太 鈴木 英之進

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.16, pp.193-201, 2001-11-01

参考文献数

13

---

This paper presents a novel decision-tree induction for a multi-objective data set, i.e. a data set with a multi-dimensional class. Inductive decision-tree learning is one of the frequently-used methods for a single-objective data set, i.e. a data set with a single-dimensional class. However, in a real data analysis, we usually have multiple objectives, and a classifier which explains them simultaneously would be useful. A conventional decision-tree inducer requires transformation of a multi-dimensional class into a singledimensional class, but such a transformation can considerably worsen both accuracy and readability. In order to circumvent this problem we propose a bloomy decision tree which deals with a multi-dimensional class without such transformations. A bloomy decision tree consists of a set of decision nodes each of which splits examples according to their attribute values, and a set of .ower nodes each of which decidesa dimension of the class for examples. A flower node appears not only at the fringe of a tree but also inside a tree. Our pruning is executed during tree construction, and evaluates each dimension of the class based on Cramér’s V. The proposed method has been implemented as D3-B (Decision tree in Bloom), and tested with eleven benchmark data sets in the machine learning community. The experiments showed that D3-B has higher accuracies in nine data sets than C4.5 and tied with it in the other two data sets. In terms of readability, D3-B has a smaller number of decision nodes in all data sets, and thus outperforms C4.5. Moreover, experts in agriculture evaluated bloomy decision trees, each of which is induced from an agricultural data set, and found them appropriate and interesting.

著者

佐藤 浩史 笠原 要 金杉 友子 天野 成昭

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.19, no.6, pp.502-510, 2004 (Released:2004-09-03)

参考文献数

26

被引用文献数

1 3

---

This paper proposes a new method for selecting fundamental vocabulary. We are presently constructing the Fundamental Vocabulary Knowledge-base of Japanese that contains integrated information on syntax, semantics and pragmatics, for the purposes of advanced natural language processing. This database mainly consists of a lexicon and a treebank: Lexeed (a Japanese Semantic Lexicon) and the Hinoki Treebank. Fundamental vocabulary selection is the first step in the construction of Lexeed. The vocabulary should include sufficient words to describe general concepts for self-expandability, and should not be prohibitively large to construct and maintain. There are two conventional methods for selecting fundamental vocabulary. The first is intuition-based selection by experts. This is the traditional method for making dictionaries. A weak point of this method is that the selection strongly depends on personal intuition. The second is corpus-based selection. This method is superior in objectivity to intuition-based selection, however, it is difficult to compile a sufficiently balanced corpora. We propose a psychologically-motivated selection method that adopts word familiarity as the selection criterion. Word familiarity is a rating that represents the familiarity of a word as a real number ranging from 1 (least familiar) to 7 (most familiar). We determined the word familiarity ratings statistically based on psychological experiments over 32 subjects. We selected about 30,000 words as the fundamental vocabulary, based on a minimum word familiarity threshold of 5. We also evaluated the vocabulary by comparing its word coverage with conventional intuition-based and corpus-based selection over dictionary definition sentences and novels, and demonstrated the superior coverage of our lexicon. Based on this, we conclude that the proposed method is superior to conventional methods for fundamental vocabulary selection.

著者

髙嶺 潮 遠藤 聡志

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.5, pp.B-KC6_1-9, 2021

---

<p>Scene understanding is a central problem in a field of computer vision. Depth estimation, in particular, is one of the important applications in scene understanding, robotics, and 3-D reconstruction. Estimating a dense depth map from a single image is receiving increased attention because a monocular camera is popular, small and suitable for a wide range of environments. In addition, both multi-task learning and multi-stream, which use unlabeled information, improve the monocular depth estimation efficiently. However, there are only a few networks optimized for both of them. Therefore, in this paper, we propose a monocular depth estimation task with a multi-task and multistream network architecture. Furthermore, the integrated network which we develop makes use of depth gradient information and can be applied to both supervised and unsupervised learning. In our experiments, we confirmed that our supervised learning architecture improves the accuracy of depth estimation by 0.13 m on average. Additionally, the experimental result on unsupervised learning found that it improved structure-from-motion performance.</p>

著者

鹿島 久嗣 坂本 比呂志 小柳 光生

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.21, no.1, pp.113-121, 2006 (Released:2006-01-06)

参考文献数

30

被引用文献数

1 1

---

We introduce a new convolution kernel for labeled ordered trees with arbitrary subgraph features, and an efficient algorithm for computing the kernel with the same time complexity as that of the parse tree kernel. The proposed kernel is extended to allow mutations of labels and structures without increasing the order of computation time. Moreover, as a limit of generalization of the tree kernels, we show a hardness result in computing kernels for unordered rooted labeled trees with arbitrary subgraph features.

著者

山田 康輔 笹野 遼平 武田 浩一

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.4, pp.B-K22_1-12, 2020

---

<p>It has been reported that a person's remarks and behaviors reflect the person's personality. Several recent studies have shown that textual information of user posts and user behaviors such as liking and reblogging the specific posts are useful for predicting the personality of Social Networking Service (SNS) users. However, less attention has been paid to the textual information derived from the user behaviors. In this paper, we investigate the effect of using textual information with user behaviors for personality prediction. We focus on the personality diagnosis website and make a large dataset on SNS users and their personalities by collecting users who posted the personality diagnosis on Twitter. Using this dataset, we work on personality prediction as a set of binary classification tasks. Our experiments on the personality prediction of Twitter users show that the textual information of user behaviors is more useful than the co-occurrence information of the user behaviors and the performance of prediction is strongly affected by the number of the user behaviors, which were incorporated into the prediction. We also show that user behavior information is crucial for predicting the personality of users who do not post frequently.</p>

著者

來村 徳信 中條 亘 笹嶋 宗彦 師岡 友紀 辰巳 有紀子 荒尾 晴惠 溝口 理一郎

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.4, pp.D-K94_1-16, 2021-07-01 (Released:2021-07-01)

参考文献数

32

---

For appropriate execution of human actions as a service, it is important to understand goals of the actions, which are usually implicit in the sequence-oriented process representations. CHARM (an abbreviation for Convincing Human Action Rationalized Model) has been proposed for representing such goals of the actions in a goal-oriented structure. It has been successfully applied for training novice nurses in a real hospital. Such a real-scale and general knowledge model, however, makes the learners difficult to understand which actions are important in a specific context such as a patient’s risk for complications. The goal of this research is to realize a context-adaptive knowledge structuring mechanism for emphasizing such actions that need special attention in a given context. As an extension of the CHARM framework, the authors have developed a general mechanism based on multi-goal action models and pathological mechanism models of abnormal phenomena. It has been implemented as a software system on tablet devices called CHARM Pad. We have also described knowledge models for the nursing domain, which include pathological mechanism models of complications with their risk factors. CHARM Pad with these models had been used by nursing students and evaluated by them through questionnaires. The result shows that CHARM Pad helped them understand the goals of nursing actions as well as finding of symptoms of complications context-adaptively.

著者

石原 一志 駒谷 和範 尾形 哲也 奥乃 博

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.20, no.3, pp.229-236, 2005 (Released:2005-03-23)

参考文献数

13

被引用文献数

2 2

---

Environmental sounds are very helpful in understanding environmental situations and in telling the approach of danger, and sound-imitation words (sound-related onomatopoeia) are important expressions to inform such sounds in human communication, especially in Japanese language. In this paper, we design a method to recognize sound-imitation words (SIWs) for environmental sounds. Critical issues in recognizing SIW are how to divide an environmental sound into recognition units and how to resolve representation ambiguity of the sounds. To solve these problems, we designed three-stage procedure that transforms environmental sounds into sound-imitation words, and phoneme group expressions that can represent ambiguous sounds. The three-stage procedure is as follows: (1) a whole waveform is divided into some chunks, (2) the chunks are transformed into sound-imitation syllables by phoneme recognition, (3) a sound-imitation word is constructed from sound-imitation syllables according to the requirements of the Japanese language. Ambiguity problem is that an environmental sound is often recognized differently by different listeners even under the same situation. Phoneme group expressions are new phonemes for environmental sounds, and they can express multiple sound-imitation words by one word. We designed two sets of phoneme groups: ``a set of basic phoneme group'' and ``a set of articulation-based phoneme group'' to absorb the ambiguity. Based on subjective experiments, the set of basic phoneme groups proved more appropriate to represent environmental sounds than the articulation-based one or a set of normal Japaneses phonemes.

著者

藤本 和則 島津 光伸

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 = Transactions of the Japanese Society for Artificial Intelligence : AI (ISSN:13460714)

巻号頁・発行日

vol.17, pp.162-165, 2002-11-01

参考文献数

8

被引用文献数

3 3

---

This paper describes availability of personal Web-pages and a prototype development for Decision Support for Internet Users, called DSIU, which is an area of research for decision support by using information on the Internet. The availability of Web-pages concerns usage of formal pages, which are provided by companies and so on, and personal pages, which are provided by private persons. Web-pages are gathered by using an Internet search engine to determine destinations for travel and personal pages are confirmed to provide much subjective information than formal pages. The prototype development concerns a travel recommendation system, which is a kind of decision support systems. The prototype uses subjective and objective information on the Internet to select several destinations for users and to provide explanations the reason why the destinations are recommended. This paper also describes our perspective of DSIU researches.

著者

玉川 奨 香川 宏介 森田 武史 山口 高平

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.29, no.4, pp.386-395, 2014-07-01 (Released:2014-06-18)

参考文献数

8

被引用文献数

2

---

Here is discussed how to build up Japanese vocabulary for Japanese Linked Open Data. The vocabulary is constructed by mapping properties of the Japanese Wikipedia Ontology to the Linked Open Vocabularies. The Japanese Wikipedia Ontology is a large scale ontology learned from the Japanese Wikipedia. It includes many properties and property relations (property domains and property ranges). The Linked Open Vocabularies is a large cloud for vocabularies of Linked Open Data. We construct a Japanese vocabulary semi-automatically by mapping properties to vocabularies. Experimental case studies show us that we can use the built Japanese vocabulary as a general vocabulary for building Japanese Linked Open Data.

著者

関 陽介

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.2, pp.C-KA3_1-10, 2021-03-01 (Released:2021-03-01)

参考文献数

21

被引用文献数

2

---

Dialogue systems, which give users quick and easy access to required information interactively, have been widely used in various fields. Dialogue systems equipped with interfaces (e.g., humanoid robots and anthropomorphic agents) have been developed in order to enhance familiarity and dialogue continuity. Related studies, in which interactive agents generate humor expressions, have also been reported. Humor is indispensable for the formation of friendly relationships between people and systems, and humor expressions can be applied in situations that generate familiar responses and provide fun to users. In this study, in order to evoke humor through dialogue, a method to generate humorous expression by asking again due to pseudo mishearing of a part of users’ queries based on examples is proposed. Specifically, a conversion candidate dictionary for humor expressions, based on Wikipedia of Japanese edition and a classification vocabulary table in which words are classified semantically, is created by word completion using distributed representation. In addition, a word conversion method is designed by approximately 1,000 mishearing survey from Twitter, and the function based on the proposed method is implemented in a dialogue system introduced into a university as a model case. In the results of the comparative evaluation with other methods quantitatively, the proposed methods gave users the most humor by converting singular and multiple words. Thus, the effectiveness of the proposed method was clarified.

著者

橋口 友哉 山本 岳洋 藤田 澄男 大島 裕明

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.1, pp.WI2-B_1-13, 2021-01-01 (Released:2021-01-01)

参考文献数

25

---

In this study, we tackle the problem of retrieving questions from a corpus archived in a Community Question Answering service that a consultant having distress can feel empathy with them. We hypothesize that the consultant feels empathy with the questions having a similar situation with that of the consultant’s distress, and propose a method of retrieving similar sentences focusing on the situation of the distress. Specifically, we propose two approaches to fine-tuning the pre-trained BERT model so that the learned model better captures the similarity of the situation between distress. One tries to extract only the words representing the situation of the distress, the other tries to predict whether the two sentences show the same situation. The data for training the models are gathered by the crowdsourcing task where the workers are asked to gather the sentences whose situation is similar to the given sentence and to annotate the words in the sentences that represent the situation. The data is then used to fine-tune the BERT model. The effectiveness of the proposed methods is evaluated with the baselines such as TF-IDF, Okapi BM25, and the pre-trained BERT. The results of the experiment with 20 queries showed that one of our methods achieved the highest nDCG@5 while we could not observe any significant differences among the methods.

著者

西 朋里 小川 祐樹 高 史明 高野 雅典 森下 壮一郎 服部 宏充

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.36, no.1, pp.WI2-E_1-9, 2021

---

<p>With the rise of Internet TV and other new media, people are now viewing the news through a variety of conduits. In addition, the influence of news media on people is changing. Viewers can post comments in Internet TV, and these comments has the viewers' opinions of the news contents. Therefore, analysis of viewers comments is important in revealing the effect of the news. In addition, these comments are posted based on the morality of the viewers, and point of view of morality is considered important in the analysis of viewer comments in news. Therefore, this study purpose is to clarify the opinion on Internet TV news programs from a moral-based analysis viewers' comments. This study analyzed the trend of viewer comments on ABEMA news programs using comment length and the application of two methods. First, the morality of viewer comments was analyzed by calculating the moral/immoral expression rate for each program using the moral foundation dictionary. Second, the distributed expressions of viewer comments (calculated by Doc2Vec) were clustered by k-means++, and program trends were analyzed using the cluster characteristics. The results indicated that there was no difference in comment length between the two program types. Comments on soft-news programs had a high moral/immoral expression rate for politics or current events. In contrast, comments of hard-news programs did not show a characteristic trend. A viewer can easily participate in the discussion, because the soft-news program deals with the same news for a long time as the news content is limited compared to the non-discussion program.</p>

著者

古池 謙人 東本 崇仁 堀口 知也 平嶋 宗

出版者

一般社団法人 人工知能学会

雑誌

人工知能学会論文誌 (ISSN:13460714)

巻号頁・発行日

vol.35, no.5, pp.C-J82_1-17, 2020-09-01 (Released:2020-09-01)

参考文献数

29

被引用文献数

1

---

Recently, the demand for programming education is increasing worldwide. Enhancing intelligent tutoringsystems (ITSs) in programming education is therefore very important. For a computer to intelligently support suchlearning, it is desirable that it be adaptive to individual learning. In ITS research, learning effectiveness is enhancedby (A) controlling features of the question or problem to be asked by indexing based on characteristics of targetdomains, or by (B) making appropriate interventions such as feedback by grasping problem-solving processes basedon explainable problem-solving models.It is important to reuse knowledge acquired through problem-solving in programming. To reuse knowledge, itis effective to first understand differences between knowledge items and then to organize that knowledge. In programming,requirements become a problem to be solved. Requirements are defined separately in the software engineeringfield as functional requirements and non-functional requirements. Functional requirements are requirements for whatis satisfied, while non-functional requirements are characteristics for satisfying the functional requirements such asinterface or security. The purpose of this study is to organize the knowledge related to this process by regarding theachievement of functional requirements as problem-solving in programming.Assuming that problem-solving is directed toward acquisition of knowledge required for a solution, descriptionsof the programming knowledge itself lead to indexing of the problem. Some studies have utilized function–behavior–structure aspects, combining each aspect to handle knowledge in parts and using them for knowledge descriptions.We have considered that the problem-solving process in this programming can be explained according tothe definition of function–behavior–structure aspects. Therefore, we proposed a model of parts based on function–behavior–structure aspects. And, we further proposed a model of the problem-solving process of parts.In order to verify the effectiveness of feedback by the proposed models, an evaluation experiment was performedin comparison with the feedback by our previous system. Feedback by the proposed models is that can begenerated based on “parts management” function and “grasp behavior of structure” function of the ITS functions thatcan be realized by the proposed model.Experiment results are suggested that the proposed models can provide more appropriate feedback that can berealized in the system, suggesting that effective support can be realized through learning of parts under the proposedmodels.In this research, by defining programming knowledge as parts, we approach various elements related to programmingthat have previously been considered tacit and clarify and organize each element independently of theprogramming language used. In this way, we try to construct a model of the problem-solving process using partsfrom the viewpoint of learning and formalize tacit knowledge.